Abstract: An information processing apparatus includes a thumbnail image generator that generates thumbnail image from content data formed of a plurality of pages, an instruction accepting section that accepts a page switching instruction, a rendering processor that generates image data to be displayed by a projector apparatus connected to the information processing apparatus, a communication section that communicates with the projector apparatus, and a controller that controls generation of data to be transmitted to the projector apparatus. The controller determines, upon acceptance of the switching instruction, the thumbnail image, transmits thumbnail image data representing the determined thumbnail image to the projector apparatus via the communication section, and then transmits high-resolution image data corresponding to the thumbnail image to the projector apparatus via the communication section.

Abstract: A method of rendering an image includes Monte Carlo rendering a scene to produce a noisy image. The noisy image is processed to render an output image. The processing applies a machine learning model that utilizes colors and/or features from the rendering system for denoising the noisy image and/or to for adaptively placing samples during rendering.

Abstract: A fingerprint sensor-compatible overlay material which uses anisotropic conductive material to enable accurate imaging of a fingerprint through an overlay is disclosed. The anisotropic conductive material has increased conductivity in a direction orthogonal to the fingerprint sensor, increasing the capacitive coupling of the fingerprint to the sensor surface, allowing the fingerprint sensor to accurately image the fingerprint through the overlay. Methods for forming a fingerprint sensor-compatible overlay are also disclosed.

Abstract: The disclosure relates to a method and to a device that recognizes road users in an environment of a vehicle. The vehicle includes at least one camera-based sensor that acquires images of the vehicle environment, wherein the device implements the method to process the images. The method includes acquiring at each of a plurality of different times, an image of an object located in the vehicle environment, performing image analyses on the images acquired at different times, and deciding, based on a result of the image analyses performed, whether the object shall be interpreted as a road user or as an inanimate entity. The device implements the method to control an autonomous driving system to control vehicle movements based on the result.

Abstract: A method for automatic registration of landmarks in 3D and 2D images of an organ comprises: using a first set of coordinates of identified first, second and third landmarks of the organ, derived from a 3D surface representation of the organ, and a second set of coordinates of the landmarks, derived from 2D laparoscopic images of the organ, to register the three landmarks as identified in the 3D surface representation with the three landmarks as identified in the 2D images. The third landmark comprises a plurality of points defining a path between two points characterizing the first and second landmarks The identification of the first, second and third landmarks in the 3D representation and the 2D images, the derivation of the first and second sets of coordinates, and the registration, based on the derived first and second sets of coordinates, are performed automatically.

Abstract: A method for facial skin age estimating and electronic device. The method includes: adjusting illumination component and color component of a facial image depending on a reference image; analyzing a plurality of evaluation index for assessing skin condition on interest area of the facial image and estimating the skin age of the facial image, according to the evaluation index.

Abstract: At least one example embodiment discloses a method of extracting a feature from an input image. The method may include detecting landmarks from the input image, detecting physical characteristics between the landmarks based on the landmarks, determining a target area of the input image from which at least one feature is to be extracted and an order of extracting the feature from the target area based on the physical characteristics and extracting the feature based on the determining.

Abstract: There is provided a display device. The display device includes a substrate including a display area that includes a first area, a plurality of pixels provided in the display area, each of the plurality of pixels provided in the display area including a first sub-pixel, a second sub-pixel and a third sub-pixel that include light emitting areas, light emitting elements disposed in the light emitting areas of the first sub-pixel, the second sub-pixel and the third sub-pixel, a touch sensor disposed on the light emitting elements to sense a touch position of a user, and a fingerprint sensor disposed in the first area to sense light emitted from the light emitting element in accordance with the touch of the user and reflected by the user. At least one of the light emitting elements is electrically connected to an adjacent light emitting element that emits light of the same color.

Abstract: An image processing method performed by a computer, the method including: changing a rendering parameter in a three-dimensional model of a recognition target; and generating teacher data of the recognition target based on the rendering parameter changed by the changing. Thereby, sufficient amount of teacher data can be obtained, without any unfavorable redundancy.

Abstract: Systems and methods for analyzing a fabric article to determine fiber damage are provided herein. In an embodiment of a method for analyzing a fabric article, the fabric article is provided and at least one image of the fabric article is captured using a three-dimensional imaging device. The at least one image is processed using a contrast function to produce a processed data set that is representative of fiber damage in a viewing area of the three-dimensional imaging device. Optionally, a processed image is produced based upon the processed data set.

Abstract: A method for healing a target region on an input image is described. A preview image is received; the preview image may reflect a down-sampled image of an original image. The method determines a target region for the preview image. The target region indicates a segment of the preview image designated for healing. The method may then heal the target region associated with the preview image using a transformation. The method may store one or more parameters associated with the healed preview image. The method may then provide for display the healed preview image to a user on a mobile device.

Abstract: One general aspect includes a memory configured to include a program and a processor configured to execute the program, where the program enables the processor to: after a first vehicle ingress/egress event, activate a sensor to capture a reference image of a portion of a vehicle body; after a second vehicle ingress/egress event, activate the sensor to capture a test image of the portion of the vehicle body; determine whether the test image includes one or more objects not found in the reference image; and release the door from the body or produce a notification or prevent vehicle movement or some combination thereof, based on the determination of whether the test image includes one or more objects not found in the reference image.

Abstract: A computing device is described which has a memory holding at least two input images depicting different parts of a panoramic scene, the images having been captured by a user moving the camera by hand to capture the panorama. The computing device has an image stitching component configured to identify, at a processor, a region of overlap between the at least two images and to calculate a displacement vector for each of a plurality of warp points in the region of overlap. The image stitching component is arranged to warp a second one of the at least two images using the warp points; and to join the warped second image to the first image.

Abstract: A method for performing real-time recognition of objects includes receiving an input video stream from a camera, pre-processing a current frame of the input video stream using one or more pre-processing layers of a neural network structure, detecting if there is an object in the current pre-processed frame using an auxiliary branch of the neural network structure, recognizing one or more objects in the current pre-processed frame using a primary branch of the neural network structure if an object is detected in the current pre-processed frame, and displaying the one or more recognized objects of the current frame in one or more bounding boxes.

Abstract: A system and method for receiving a medical image, receiving an adaptation of a model of a physical structure, the adaptation relating to the medical image, determining an image quantity of the medical image at each of a plurality of vertices of the adaptation and aggregating the plurality of image quantities to determine an evaluation metric.

Abstract: An electronic device and method are disclosed herein. The electronic device includes a display, a fingerprint recognition sensor configured to recognize a fingerprint received through the display, and a processor. The processor is configured to implement the method, which includes detecting a fingerprint using a fingerprint recognition sensor of the electronic device through a display of the electronic device; and controlling the display to display at least one object based on the fingerprint.

Abstract: Systems and methods of training vehicles to improve performance, reliability and autonomy of vehicles. Sensors capture a vehicle driver's eye movements, hand grip and contact area on steering wheel, distance of the accelerator and brake pedals from the foot, depression of these pedals by the foot, and ambient sounds. Data from these sensors is used as training data to improve autonomy of vehicles. Detection of events occurring outside a vehicle is made by comparing human sensor data with an associated road map to determine correlation. Signatures corresponding to human reactions and actions are extracted, which also incorporate data acquired using vehicle and outside environment sensors. By scoring driver responses to events outside the vehicle as well as during non-events, expert drivers are identified, whose responses are used as a part of vehicle training data.

Abstract: The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned semantic segmentation model to determine a crop residue parameter value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.

Abstract: An image processing apparatus includes: an acquisition unit configured to acquire a plurality of images each capturing an identical target and having a different attribute; a derivation unit configured to derive features from the plurality of images, using a first neural network; an integration unit configured to integrate the features derived from the plurality of images; and a generation unit configured to generate a higher quality image than the plurality of images from the feature integrated by the integration unit, using a second neural network.

Abstract: A device configured to emulate image mapping in a correlithm object processing system comprises a memory and one or more processors. The memory stores a correlithm object mapping table configured with multiple source image elements and multiple corresponding target correlithm objects. The processors receive an input image element comprising an n-pixel array of binary values and determine n-dimensional distances between the input image element and each of the source image elements. The processors then identify a source image element with the closest determined n-dimensional distance. The processors determine whether a deviation between the input image element and the identified source image element is within a predetermined tolerance. The processors identify a target correlithm object corresponding to the identified source image and determine a perturbation to be applied to the identified target correlithm object based on the determined deviation.