Abstract: The technology described herein is directed to systems, methods, and software for indexing video. In an implementation, a method comprises identifying one or more regions of interest around target content in a frame of the video. Further, the method includes identifying, in a portion of the frame outside a region of interest, potentially empty regions adjacent to the region of interest. The method continues with identifying at least one empty region of the potentially empty regions that satisfies one or more criteria and classifying at least the one empty region as a negative sample of the target content. In some implementations, the negative sample of the target content in a set of negative samples of the target content, with which to train a machine learning model employed to identify instances of the target content.

Abstract: An example system for generating stereoscopic light field panoramas includes at least one memory; and at least one processor to execute instructions to: access images of a scene captured by a plurality of cameras, the images including light field information associated with the scene; generate, based on first portions of the images, a first stereoscopic light field panorama for a first perspective associated with a left eye viewpoint of the scene, the left eye viewpoint associated with a left eye position on a first circle; and generate, based on second portions of the images, a second stereoscopic light field panorama for a second perspective associated with a right eye viewpoint of the scene, the right eye viewpoint associated with a right eye position on a second circle, the first circle being different than and concentric to the second circle.

Abstract: When one or multiple video files that correspond to at least a part of preset sections are read out from a storage unit, a length of time of a section overlap, which represents a time slot that overlaps the section among from one or more time slots over which the read video file(s) are recorded, is calculated, and the video file(s) that corresponds to the time code contained in the section overlap having been subjected to calculation are clipped and stored in a predetermined storage area, the medical video processing system can carry out, when the length of time of the section overlap (for example, 32 minutes and 10 seconds) exceeds a predetermined length of time (for example 30 minutes), a shortening process that shortens the length of time of the video file(s) to be stored in the predetermined storage area, down to a predetermined length of time or shorter.

Abstract: System and method to recognise characters from an image are disclosed. The method includes receiving the at least one image, pre-processing the at least one image, extracting a plurality of characters from the corresponding at least one image, extracting at least one structure from the corresponding at least one image upon applying an edge detection technique to extract a structure, identifying a template based on extracted structure, subjecting the plurality of characters into a plurality of ensemble AI models to extract one of a plurality of texts, a plurality of non-textual data and a combination thereof, comparing a plurality of extracted plurality of texts, a plurality of non-textual data, or a combination thereof from the corresponding plurality of ensemble AI models with each other, generating a confidence score and validating one of the plurality of accurate texts, the plurality of accurate non-textual data, or a combination thereof.

Abstract: A method includes receiving one or more panoramic image processing parameters from a remote terminal, controlling a carrier to rotate an image capturing device about a first axis of the carrier while causing the image capturing device to capture a plurality of images based at least in part on the one or more panoramic image processing parameters, and stabilizing the image capturing device against motions with respect to a second axis or a third axis of the carrier while the image capturing device is rotating about the first axis of the carrier. The image capturing device is coupled to an unmanned aerial vehicle (UAV) via the carrier.

Abstract: In an illustrative embodiment, systems for designing and producing customized food products include receiving a request to design a customized food product containing a printed edible medium. The systems may calculate, based on product inventory at a preferred bakery, a preparation lead time for the food product where the product inventory includes availability of printed edible media substrates. The systems may present customization user interface screens that provide customization options for the food product. The systems may convert customization option selections made at the customization user interface screens into decorating instructions for the food product and transmit the decorating instructions to the bakery. The systems may determine a position in a preparation queue for the food product based in part on attributes of pending food product orders in a preparation queue at the bakery.

Abstract: The present disclosure includes a video transmission apparatus, a video reception apparatus, an image transmission apparatus, an image reception apparatus, and a system. The image transmission apparatus includes a detection circuitry, a generation circuitry, and a transmission circuitry. The generation circuitry is configured to generate a first image based on a first piece of positional information from a plurality of pieces of positional information, the first image including the overlap region and corresponding to a first region of interest of two or more regions of interest. The generation circuitry is also configured to generate one or more second images based on an overlap region and the plurality of pieces of positional information, the one or more second images excluding the overlap region and corresponding to regions of interest other than the first region of interest of the two or more regions of interest.

Abstract: What is described are a method and a device, wherein two types of individual images are captured, namely a set of individual images captured simultaneously, and a further set of individual images captured in temporal succession. Among said two sets of individual images, individual images are selected which in combination result in a panoramic image.

Abstract: A user device may capture a plurality of preview images that each include image data. The user device may process, in substantially real-time, a preview image to identify an object in the preview image, including determining an outline of the object. The user device may create a mask that hides a portion of the image data associated with an area outside of the outline of the object in one or more of the preview images. Based on determining that a parameter associated with glare of the object in the preview images does not satisfy a threshold, the user device may provide, in substantially real-time, feedback to a user, including an instruction to the user to perform an action with respect to the user device or to the object, and, based on determining that the parameter satisfies the threshold, the user device may automatically capture an image of the object.

Abstract: An electronic device performs HDR processing by using a plurality of image sensor blocks including a first image sensor block that photographs an object at a first field of view and a second image sensor block that photographs the object at a second field of view greater than the first field of view. An image signal processor generates first image data and second image data based on the photographed object. A main processor crops image data among image data of the second sensor that correspond to image data of the first sensor, and performs HDR processing based on the first image data and the cropped second image data.

Abstract: An image processing apparatus comprises: at least one processor or circuit configured to perform the operations of following units: an obtaining unit configured to obtain a plurality of image signals being composed of image signals shot wider different shooting conditions; a determination unit configured to determine a composition rate in order to composite an image signal that has the predetermined shooting condition with a noise-reduced image that has the predetermined shooting condition, in accordance with an inter-frame change amount and a parameter indicating the predetermined shooting condition; a noise reduction unit configured to composite the image signal with the noise-reduced image using the composition rate to generate a new noise-reduced image; and a composition unit configured to composite the new noise-reduced image and an image signal that has another shooting condition.

Abstract: Computer systems and methods are described for automatically generating a 3D model, including, with computer processor(s), obtaining geo-referenced images representing the geographic location of a structure containing one or more real façade texture of the structure; locating a geographical position of real façade texture(s) of the structure; selecting base oblique image(s) from the images by analyzing image raster content of the real façade texture depicted in the images with selection logic; analyzing the real façade texture to locate a geographical position of at least one occlusion using pixel pattern recognition of the real façade texture; locating oblique image(s) having an unoccluded image characteristic of the occlusion in the real façade texture; applying the real façade texture to wire-frame data of the structure to create a 3D model of the structure; and applying the unoccluded image characteristic to the real façade texture to remove the occlusion from the real façade texture.

Abstract: A method for shooting image, applied to an electronic device in which an image capturing device is mounted, includes: receiving a first input from a user; responsive to the first input, acquiring a first image and a second image captured by the image capturing device for a target object, a framing range of the first image being same as a framing range of the second image; and performing synthesis processing on the first image and the second image to generate a target image, the target image including a first object image of the target object in the first image and a second object image of the target object in the second image.

Abstract: Provided is an electronic apparatus and method for providing an image of surroundings of a vehicle. The electronic apparatus for providing an image of surroundings of the vehicle includes a first image sensor creating a first image by capturing surroundings of the vehicle; a second image sensor creating a second image by capturing surroundings of the vehicle; and a processor configured to obtain feature information of each of the first image and the second image and use a portion of the first image and a portion of the second image to create a composite image that represents the surroundings of the vehicle, based on the obtained feature information.

Abstract: The present invention provides a target object elimination method based on a panoramic camera, the panoramic camera comprising at least two independent lenses, wherein the method comprises following steps: capturing one basic panoramic image by each of the independent lenses; recognizing a target object from each of the basic panoramic images; dividing each of the basic panoramic images into a plurality of image parts having a same or different size, wherein at least one of the image parts comprises the target object; deleting the one image part comprising the target object in each of the basic panoramic images; and combining all remaining image parts in each of the basic panoramic images to obtain a corrected panoramic image from which the target object is eliminated. By the present invention, the target object can be eliminated quickly and efficiently while ensuring the quality of the image.

Abstract: An image processing method that generates high-resolution image data from low-resolution image data and an image receiving apparatus that is operated by the image processing method are provided. In the image processing method that generates high-resolution image data from low-resolution image data, the low-resolution image data is divided to generate a plurality of first image data, among the plurality of first image data, one of two adjacent image data is second image data, and the other is third image data. Surroundings of the second image data are supplemented with pixel data to generate fourth image data. The pixel data includes part of the third image data. A convolutional neural network using the fourth image data as an input is implemented, fifth image data is output from the convolutional neural network, and a plurality of the fifth image data is combined to generate high-resolution image data. The image receiving apparatus is operated by the image processing method.

Abstract: An autonomously motile device is capable of capturing image data, such as panoramic images, as it moves to different locations in an environment. It selects the locations at which to capture the image data by determining, for each of a plurality of grid units in a map of the environment, a number of grid points that are unobstructed by a wall or object surrounding the point. It then selects a number of locations having the greatest number of viewable grid points.

Abstract: Disclosed herein are display techniques that will allow sensitive data displayed on a computer screen to only be viewed by authorized users and will render computer screen unreadable to unauthorized users. One or more display techniques are capable of automatically scrambling and unscrambling display screen of the computing device in which only an intended viewer is able to view data on the display screen using deciphering glasses.

Abstract: Technologies relating to system and method of real-time video overlaying or superimposing display from multiple mutually synchronous cameras are disclosed. An example method of real-time video overlaying includes the steps of: synchronizing frame rates of a depth data, a face meta data, and a video data of a first camera video output captured by a first camera; determining a first depth between a user face and the first camera; using a cutoff depth to determine a user body contour; generating a binary mask of the user body contour based on the first depth and the cutoff depth; smoothing an edge of the binary mask; merging the binary mask with the first camera video output and generating a merged first camera video output; and overlaying the merged first camera video output onto a second camera video output.

Abstract: An image decoding method according to the present invention comprises the steps of: generating a merge candidate list in a current block; specifying one of a plurality of merge candidates included in the merge candidate list; deriving a first affine seed vector and a second affine seed vector of the current block on the basis of a first affine seed vector and a second affine seed vector of the specified merge candidate; deriving an affine vector for a subblock in the current block, using the first affine seed vector and the second affine seed vector of the current block; and performing motion compensation prediction for the subblock on the basis of the affine vector.

Abstract: An oblique imagery application receives an oblique image captured by an oblique camera at a non-orthogonal angle with respect to a ground plane and map data including a map tile corresponding to geographic coordinates. A principal axis is determined that is orthogonal to an image plane defined by the oblique image and intersecting a center of the oblique image. For each pixel of the oblique image, a pixel vector is determined and a set of deviation coordinates based on a deviation of the pixel vector from the principal axis is determined for the pixel, with the pixel vector of a pixel passing through a focal point of the oblique camera and ending at the pixel. The map tile is associated to the pixels of the oblique image based on the camera parameters, the deviation coordinates of the pixels, the oblique camera parameters, and the geographic coordinates of the map tile.

Abstract: A method includes generating image signals from which a two-dimensional image is generated. The method includes generating object image signals by capturing an examination object arranged in a space. The method includes generating overview image signals by capturing an overview of the space. The method includes receiving image information included in the generated object image signals and the generated overview image signals. The method includes combining a two-dimensional object image, generated from the object image signals, with a two-dimensional perspectively distorted overview image of the space, generated from the overview image signals, to form a two-dimensional output image. The method includes scaling the received image information with respect to an image size for forming the output image in a manner such that at least one dimension of the examination object captured both in the object image and in the overview image has a same size in the output image.

Abstract: There is provided an information processing apparatus and method and a program that enable grasping of a missing in an image. A missing determination unit determines whether or not there is a missing portion in an image captured by a plurality of cameras, and supplies a determination result (presence or absence of a missing) to a display control unit. The display control unit controls notification according to the determination result (presence or absence of a missing). The present disclosure can be applied to, for example, a system for causing a circumference image from an image captured by a wearable terminal to be displayed in another wearable terminal.

Abstract: Perception sensors of a vehicle can be used for various operating functions of the vehicle. A computing device may receive sensor data from the perception sensors, and may calibrate the perception sensors using the sensor data, to enable effective operation of the vehicle. To calibrate the sensors, the computing device may project the sensor data into a voxel space, and determine a voxel score including an occupancy score and a residual value for each voxel. The computing device may then adjust an estimated position and/or orientation of the sensors, and associated sensor data, from at least one perception sensor to minimize the voxel score. The computing device may calibrate the sensor using the adjustments corresponding to the minimized voxel score. Additionally, the computing device may be configured to calculate an error in a position associated with the vehicle by calibrating data corresponding to a same point captured at different times.

Abstract: The disclosure describes various embodiments for online system-level validation of sensor synchronization. According to an embodiment, an exemplary method of analyzing sensor synchronization in an autonomous driving vehicle (ADV) include the operations of acquiring raw sensor data from a first sensor and a second sensor mounted on the ADV, the raw sensor data describing a target object in a surrounding environment of the ADV; and generating an accuracy map based on the raw sensor data in view of timestamps extracted from the raw sensor data. The method further includes the operations of generating a first bounding box and a second bounding box around the target object using the raw sensor data; and performing an analysis of the first and second bounding boxes and the accuracy map using a predetermined algorithm in view of one or more pre-configured sensor settings to determine whether the first sensor and the second sensor are synchronized with each other.

Abstract: A method and device for acquiring a target object, and a robot are provided. The method includes: acquiring a plurality of frames of continuous images in video images, where each frame of image includes a first target object; acquiring, based on the continuous images including the first target object, a first target image from which a background has been removed; acquiring, based on a distance from a first center point of the first target image to a common boundary, a location of a second target object in the first target image, where the first center point is determined based on a color of the second target object, the common boundary is an overlapping boundary of the second target object and the first target object, and the second target object is included in the first target object; and extracting the second target object based on the location of the second target object in the first target image.

Abstract: An electronic device, method, and computer readable medium for compositing high dynamic range frames are provided. The electronic device includes a camera, and a processor coupled to the camera. The processor registers the plurality of multi-exposure frames with a hybrid of matched features to align non-reference frames with a reference frame; generates blending maps of the plurality of multi-exposure frames to reduce moving ghost artifacts and identify local areas that are well-exposed in the plurality of multi-exposure frames; and blends the plurality of multi-exposure frames weighted by the blending maps using a two-step weight-constrained exposure fusion technique into a high dynamic range (HDR) frame.

Abstract: An object of an image processing apparatus, a method, and a non-transitory computer readable recording medium storing a program is to enable acquisition of a composite image in which an effect of a meniscus formed on a liquid surface of a liquid in a container is reduced. A plurality of captured images acquired by setting a part of adjacent observation regions to overlap with each other and imaging a container a plurality of times while changing a position of the observation region are acquired. An overlapping region selection unit 51 selects the captured image having a highest contrast in the overlapping region with at least one adjacent captured image in each captured image Gi as an image of the overlapping region. A composite image generation unit 52 generates a composite image Gs by linking the plurality of captured images in which the images of the overlapping regions are selected.

Abstract: An image processing system includes an image obtaining unit that obtains images based on capturing from plural directions by plural cameras, an information obtaining unit that obtains viewpoint information indicating a virtual viewpoint, and a generation unit configured to generate virtual viewpoint images on a basis of the obtained images and viewpoint information. The generation unit generates a first virtual viewpoint image outputted to a display apparatus that displays an image for a user to specify a virtual viewpoint and a second virtual viewpoint image outputted to an output destination different from the display apparatus by using at least one of data generated in a process for generating the first virtual viewpoint image by image processing using the plural images obtained by the image obtaining unit and the first virtual viewpoint image, the second virtual viewpoint image having a higher image quality than that of the first virtual viewpoint image.

Abstract: A method and apparatus of image stitching using confidence level of image matching on image pair to be stitched are disclosed. According to the present invention, the first quality of image matching is determined for a current image based on feature matching on first image pairs corresponding to the current image and a neighboring image set. If the first quality of image matching for at least one first image pair satisfies a first quality criterion, then the second quality of image matching is determined based on pixel-domain matching for one or more candidate image pairs, where each candidate image pair has a corresponding first quality of image matching satisfying the first quality criterion. If the second quality of image matching for a candidate image pair satisfies a second quality criterion, then the matched image pair is stitched.

Abstract: A method and apparatus for constructing a 3D scene model are provided. The method includes: acquiring a first point cloud corresponding to a current target scene (S101); determining a first partial point cloud corresponding to a dynamic object from the first point cloud (S102); constructing a foreground 3D model based on the first partial point cloud (S103); and superimposing the foreground 3D model with a background 3D model to obtain a current 3D scene model (S104). As can be seen, it is not necessary to fuse each pixel acquired by each depth camera. Instead, the dynamic object is determined in the point cloud acquired by the depth camera. Only the foreground 3D model corresponding to the dynamic object is superimposed with the background 3D model corresponding to the static objects obtained in advance. This reduces the amount of computation to build a 3D scene model.

Abstract: A system control unit sets at least one of a non-overlapped area in which an nth image and an (n+1)st image do not overlap and a low contrast area of the (n+1)st image as an in valid area that is not used for misalignment detection of the (n+1)st image. Then, the system control unit sets alignment small blocks for a motion vector search in only an area excluding the invalid area in the overlapped area in which two combining target images overlap.

Abstract: A control method for an image processing apparatus that generates a plurality of pieces of album data corresponding to a plurality of albums includes automatically selecting at least one piece of image data out of a plurality of pieces of image data as common image data corresponding to an image to be placed in a common page, which is a page common to all of the plurality of albums, based on an evaluation that is based on a first factor, and automatically selecting at least one piece of image data out of the plurality of pieces of image data as individual image data corresponding to an image to be placed in an individual page, which is a page not common to all of the plurality of albums, based on an evaluation that is based on a second factor.

Abstract: A digital graduated filter is implemented in an imaging device by combining multiple images of the subject wherein the combining may include combining different numbers of images for highlights and for shadows of the subject. The imaging device may present a user with a set of pre-defined graduated filter configurations to choose from. A user may also specify the direction of graduation and strength of graduation in a viewfinder. In an alternative implementation, combining may include scaling of pixels being added instead of varying the number of images being combined. In an alternative implementation, the combining of multiple images may include combining a different number of images for highlights of the subject than for shadows of subject.

Abstract: Methods, apparatus, and processor-readable storage media for dynamic digital information retrieval are provided herein. An example computer-implemented method includes training a machine learning object detection model using server component images and one or more features of the server component images; determining a type of server device captured by at least one camera-derived input, wherein determining the type of server device comprises analyzing the at least one camera-derived input using the machine learning object detection model; identifying one or more server components captured by the at least one camera-derived input by analyzing, within a context of the determined type of server device, the at least one camera-derived input using the machine learning object detection model; and outputting, to at least one display, information pertaining to the identified server components, wherein the information is retrieved from a data source related to the determined type of server device.

Abstract: An attitude estimation apparatus (30) includes: a data acquiring unit (32) for acquiring observation data; a range-measurement point coordinate calculator (33A) for calculating geodetic coordinates of a range-measurement point in a geodetic coordinate system using positioning data, ranging data, actual attitude data, and an estimated value of an unknown parameter representing an attitude of a flying object; an image coordinate calculator (33B) for calculating coordinates of a projected point by performing projection transformation from the geodetic coordinate system to an image coordinate system on the geodetic coordinates; an image matching processor (34) for detecting image coordinates of the range-measurement point appearing in a first captured image by executing image matching between the first captured image and a second captured image selected from captured images; and an attitude estimator (35) for correcting the estimated value such that a magnitude of a difference between the coordinates of the proje

Abstract: An image processing method and apparatus, a storage medium and an electronic device are disclosed. The method comprises: acquiring a first face image in a real scene and a second face image in a virtual scene, wherein the second face image is generated at least according to a first value of at least one target parameter, and the at least one target parameter is used for determining at least one attribute of a face image in the virtual scene; extracting at least one first image feature from the first face image, and extracting at least one second image feature from the second face image; acquiring a similarity between the at least one first image feature and the at least one second image feature; adjusting the first value of the at least one target parameter based on the similarity to obtain a target value of the at least one target parameter; and rendering the at least one target parameter according to the target value to obtain the target face image in the virtual scene.

Abstract: An image processing system includes an image obtaining unit that obtains images based on capturing from plural directions by plural cameras, an information obtaining unit that obtains viewpoint information indicating a virtual viewpoint, and a generation unit configured to generate virtual viewpoint images on a basis of the obtained images and viewpoint information. The generation unit generates a first virtual viewpoint image outputted to a display apparatus that displays an image for a user to specify a virtual viewpoint and a second virtual viewpoint image outputted to an output destination different from the display apparatus by using at least one of data generated in a process for generating the first virtual viewpoint image by image processing using the plural images obtained by the image obtaining unit and the first virtual viewpoint image, the second virtual viewpoint image having a higher image quality than that of the first virtual viewpoint image.

Abstract: A method may include acquiring, via a capture system, a dataset associated with a user at a first location, detecting, via a control system, the user at a second location, displaying, via an environmental system, one or more images generated from the dataset at the second location in response to detecting the user at or past the second location, and triggering, via a special effect system, a special effect during the displaying at the second location in response to detecting the user at or past the second location. The dataset may include image data of the user.

Abstract: A three-dimensional imaging system for generating a 3D panoramic video/image is disclosed. The three-dimensional imaging system includes a plurality of stereoscopic pairs of compound cameras which are separated by a predefined distance d. The imaging system is configured to operate in a first mode to generate panoramic images simultaneously using the compound cameras. Spatial distortion and temporal distortion are calculated for each column in a region of overlap of the field of view of the panoramic images generated. The column for which the spatial and temporal distortion is minimum is marked as a seam location. The marked seam location is changed based on location of a motion in the column for which the calculated spatial and temporal distortion is minimum.

Abstract: Generating thumbnails from panoramic images is described. In one or more implementations, a 2D projection of a panoramic image is received and projected onto a 3D surface to generate a 3D projection. Portions of the 3D projection are formed, and each portion is projected to a 2D plane to generate 2D projections of the portions. Object recognition is then performed on the portions that identifies objects, attributes of the objects, and locations of the objects within the panoramic image. Responsive to an image search query matching one of the recognized objects, the system generates a thumbnail from the panoramic image specific to a portion of the panoramic image that contains the object and outputs the thumbnail.

Abstract: A method of localizing an object includes capturing a first image of the object from a first camera position, performing edge detection on the first image to form an edge-detected second image, and performing a distance transform on the second image to form a distance transformed third image. A virtual camera is positioned in virtual space relative to a virtual model of the object, and an edge-detected fourth image of the virtual model of the object is generated. An alignment cost is generated of the edge-detected fourth image of the virtual model relative to the edge-detected second image of the object, and a position of the virtual camera is transformed to a position having a lower alignment cost than the alignment cost. A physical location of the object is estimated based on the transformed virtual camera position.

Abstract: A system is provided for identifying damages of a vehicle. During operation, the system can obtain a set of digital images associated with a set of tagged digital images as training data. Each tagged digital image in the set of tagged digital images may include at least one damage object. The system can train a damage identification model based on the training data. When training the damage identification model, the system may identify at least a damage object in the training data based on a target detection technique. The system may also generate a set of feature vectors for the training data. The system can use the set of feature vectors to optimize a set of parameters associated with the damage identification model to obtain a trained damage identification model. The system can then apply the trained damage identification model to obtain a damage category prediction result.

Abstract: The present disclosure relates to a method for removing an object to be processed from an image and a device for performing the method. A method for removing an object to be processed from an image can comprise the step of: an image processing device deciding an object to be processed in an image; and the image processing device performing image post-processing with respect to the object to be processed, wherein the object to be processed can be an object which is unintentionally captured.

Abstract: A method of decoding a bitstream by an electronic device is provided. An image frame is received from the bitstream. A block unit is determined from the received image frame. A plurality of model parameters is derived based on motion information of a plurality of neighboring blocks neighboring the block unit. An intermediate block is derived for a sub-block in the block unit based on the plurality of model parameters. A vector formula is determined based on the plurality of model parameters, and at least one vector value is calculated based on the vector formula for at least one sampling position in the sub-block. The at least one vector value is compared with a threshold to determine whether the intermediate block is adjusted based on the vector formula to generate a predicted block. The sub-block is reconstructed based on the predicted block.

Abstract: An automated process empirically normalizes a “dark” image by adjusting the apparent exposure to compensate for nonlinearity in the luminance response of the image sensor. The process includes receiving at least two digital images, one of the digital images having an exposure value that is greater than that of another of the digital images. A reduced-resolution pair of images is produced from the at least two digital images. At least one representative scale factor is calculated from tonal values in the two images and at least one empirical scale factor is determined by selective interpolation between the representative scale factor and a comparative scale factor. The empirical scale factor is used in a function applied pixelwise to the darker of the digital images to produce an empirically normalized digital image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving, by an image signal processor, one or more input image signals from one or more image sensors; determining a mapping based on the input image signal(s), wherein the mapping includes records that associate image portions of an output image with corresponding image portions of the input image signal(s); sorting the records of the mapping according to an order of the corresponding image portions of the input image signal(s); applying, by the image signal processor, image processing to image portions of the input image signal(s) to determine image portions of one or more processed images in the order; and determining, by the image signal processor, the image portions of the output image based at least in part on the mapping and the corresponding image portions of the processed image(s) in the order.

Abstract: Methods, apparatus, systems, and computer program products for displaying captured screenshots are disclosed herein. One method includes capturing, by an information handling device, a set of screenshots of a main display screen of a computing device and displaying the captured set of screenshots on a sub-display screen of the computing device. Apparatus, systems, and computer program products that include and/or perform the methods are also disclosed herein.

Abstract: A method and a fault-tolerant computer architecture (FCTA) for fail-safe trajectory planning for a moving entity (MOV). The method and FCTA uses a commander (COM), a monitor (MON), and a safe envelope generating stage (ENV). Based on sensor input, the commander (COM) and the monitor (MON) produce real-time images of objects (OBJ1, OBJ2) detected. A trajectory planning stage (TRJ-PLN) generates trajectories (COM-TRJ1, COM-TRJ2), and the safe envelope generating stage (ENV) generates a safety envelope. The commander (COM) provides the one or more trajectories (COM-TRJ1, COM-TRJ2) to the monitor (MON) and the decision subsystem (DECIDE). A trajectory verification stage (TRJ-VRFY) verifies a trajectory (COM-TRJ1, COM-TRJ2) generated by the commander (COM) only if said trajectory (COM-TRJ1, COM-TRJ2) is completely located inside said safety envelope. A moving entity (MOV) uses a trajectory (COM-TRJ1, COM-TRJ2) generated by the commander (COM) only when said trajectory is verified by the monitor (MON).

Abstract: A method performed by a vehicle system for handling images of the surroundings of a vehicle. An image of the surroundings of the vehicle is obtained. The image is obtained from at least one side image capturing device mounted in or on the vehicle, and the image capturing device comprises a fisheye camera lens. At least a part of the distortions in the image is corrected to obtain a corrected image. The corrected image is rotationally transformed using a first rotational transformation to obtain a first transformed image. The corrected image is rotationally transformed using a second rotational transformation to obtain a second transformed image. The first and second transformed images are consecutive or adjacent images.