Abstract: The disclosure relates to a method for correcting a movement of an object occurring during an MR image acquisition. The method includes: determining a motion model describing possible movements of the object based on a defined number of degrees of freedom; detecting a motion of a marker provided on the object with a motion sensor; determining a description of the motion model in a common coordinate system; determining the motion of the marker in the common coordinate system; determining a first motion of the object in the common coordinate system using the description of the motion model, the first motion being the motion that best matches the determined motion of the marker in the common coordinate system using the defined number of degrees of freedom; and correcting the movement of the object based on the determined first motion in order to determine at least one motion corrected MR image.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly generating modified digital images utilizing a guided inpainting approach that implements a patch match model informed by a deep visual guide. In particular, the disclosed systems can utilize a visual guide algorithm to automatically generate guidance maps to help identify replacement pixels for inpainting regions of digital images utilizing a patch match model. For example, the disclosed systems can generate guidance maps in the form of structure maps, depth maps, or segmentation maps that respectively indicate the structure, depth, or segmentation of different portions of digital images. Additionally, the disclosed systems can implement a patch match model to identify replacement pixels for filling regions of digital images according to the structure, depth, and/or segmentation of the digital images.

Abstract: A video quality improvement method may comprise: inputting a structure feature map converted from current target frame by first convolution layer to first multi-task unit and second multi-task unit, which is connected to an output side of first multi-task unit, among the plurality of multi-task units; inputting a main input obtained by adding the structure feature map to a feature space, which is converted by second convolution layer from those obtained by concatenating, in channel dimension, a previous target frame and a correction frame of the previous frame to first multi-task unit; and inputting current target frame to Nth multi-task unit connected to an end of output side of second multi-task unit, wherein Nth multi-task unit outputs a correction frame of current target frame, and machine learning of the video quality improvement model is performed using an objective function calculated through the correction frame of current target frame.

Abstract: A method, apparatus and system for video display and a camera are disclosed. The camera includes one wide-field lens assembly and a wide-field sensor corresponding to the wide-field lens assembly; at least one narrow-field lens assembly and narrow-field sensor corresponding to the narrow-field lens assembly, wherein an angle of view of the wide-field lens assembly is greater than an angle of view of the narrow-field lens assembly, and for a same target, a definition of the wide-field sensor is smaller than that of the narrow-field sensor; and a processor configured for performing human body analysis on the wide-field image and performing face analysis, head and shoulder analysis or human body analysis on at least one frame of narrow-field image. The methods, apparatuses and systems can reduce the workload of installing and adjusting the cameras during monitoring, the performance requirements for the server, and monitoring costs.

Abstract: A computer-implemented method for high resolution image inpainting comprising the following steps: providing a high resolution input image, providing at least one inpainting mask, selecting at least one rectangular sub-region of the input image and at least one aligned rectangular subregion of the inpainting mask such that the rectangular subregion of the input image encompasses at least one set of pixels to be removed and synthetized, the at least one sub-region of the input image and its corresponding aligned subregion of the inpainting mask having identical minimum possible size and a position for which a calculated information gain does not decrease, processing the sub-region of the input image and its corresponding aligned subregion of the inpainting mask by a machine learning model, generating an output high resolution image comprising the inpainted sub-region.

Abstract: A method may include determining, based at least on an image of a document, a plurality of text bounding boxes enclosing lines of text present in the document. A machine learning model may be trained to determine, based at least on the coordinates defining the text bounding boxes, the coordinates of a document bounding box enclosing the text bounding boxes. The document bounding box may encapsulate the visual aberrations that are present in the image of the document. As such, one or more transformations may be determined based on the coordinates of the document bounding box. The image of the document may be deskewed by applying the transformations. One or more downstream tasks may be performed based on the deskewed image of the document. Related methods and articles of manufacture are also disclosed.

Abstract: An eye state detecting method, applied to an electronic apparatus with an image sensor, which comprises: (a) acquiring a detecting image via the image sensor; (b) defining a face range on the detecting image; (c) defining a determining range on the face range; and (d) determining if the determining range comprises an open eye image or a close eye image.

Abstract: A method for generating a dense light detection and ranging (LiDAR) representation by a vision system includes receiving, at a sparse depth network, one or more sparse representations of an environment. The method also includes generating a depth estimate of the environment depicted in an image captured by an image capturing sensor. The method further includes generating, via the sparse depth network, one or more sparse depth estimates based on receiving the one or more sparse representations. The method also includes fusing the depth estimate and the one or more sparse depth estimates to generate a dense depth estimate. The method further includes generating the dense LiDAR representation based on the dense depth estimate and controlling an action of the vehicle based on identifying a three-dimensional object in the dense LiDAR representation.

Abstract: A vehicle position determination device mountable to a vehicle, the vehicle position determination device including an acquisition unit that acquires a surrounding image that is road information for identifying a position of the vehicle and is represented by a small displacement with respect to the vehicle, and a control unit that compares the road information with road characteristic information indicating an absolute position of a predetermined point and determines a vehicle position according to a result of the comparison; the road information includes at least one of road shape information indicating a shape of a road surface in a direction of travel of the vehicle and road pattern information indicating a pattern on a road surface.

Abstract: The present invention provides a processing apparatus (20) including a first generation unit (22) that generates, from a plurality of time-series images, three-dimensional feature information indicating a time change of a feature in each position in each of the plurality of images, a second generation unit (23) that generates person position information indicating a position in which a person is present in each of the plurality of images, and an estimation unit (24) that estimates person behavior indicated by the plurality of images, based on the time change of the feature indicated by the three-dimensional feature information in the position in which the person is present being indicated by the person position information.

Abstract: Image processing methods are provided. One of the method includes: obtaining a to-be-processed multi-channel feature maps; obtaining multi-channel first output feature maps and multi-channel second output feature maps by processing the multi-channel feature maps through a parallel pointwise convolution and non-pointwise operation, where the non-pointwise convolution is for descripting a spatial feature of each channel and an information exchange between the feature maps; and fusing the multi-channel first output feature maps and the multi-channel second output feature maps to obtain a multi-channel third output feature map.

Abstract: A method and system for calculating a minimum distance from a robot to dynamic objects in a robot workspace. The method uses images from one or more three-dimensional cameras, where edges of objects are detected in each image, and the robot and the background are subtracted from the resultant image, leaving only object edge pixels. Depth values are then overlaid on the object edge pixels, and distance calculations are performed only between the edge pixels and control points on the robot arms. Two or more cameras may be used to resolve object occlusion, where each camera's minimum distance is computed independently and the maximum of the cameras' minimum distances is used as the actual result. The use of multiple cameras does not significantly increase computational load, and does require calibration of the cameras with respect to each other.

Abstract: A device and a method for projecting image data onto a projection surface of a vehicle windowpane of a vehicle. An image data processing unit generates second image data from first image data based on recorded surroundings brightness of the vehicle. A gradation curve is used to generate the second image data in such a way that dark image regions of the first image data lying below a predetermined color brightness threshold compared to image regions lying above the color brightness threshold in the first image data are brightened in the second image data compared to the first image data with regard to color or greyscale spectra. A degree of brightening of the dark image regions in the first image data increases with an increase in the recorded surroundings brightness.

Abstract: Methods and apparatus for processing images captured by cameras for use in stereo depth determinations are described and/or for using depth information generated by processing such images is described. Images are captured using a reference camera and at least one additional camera. Filtering is implemented as part of a patch matching process to reduce the risk of erroneous matches, e.g., due to image blur in one image but not another. The filtering may be, and sometimes is, implemented on a patch basis. A candidate patch is generated by filtering a portion of an image captured by a camera, e.g., a second camera by performing a sharpening or blurring operation to a portion of the image to generate a candidate patch. The amount of blurring or sharpening that is applied to generate the candidate patch depends, in some embodiments, on the relative difference between the candidate patch and the reference patch.

Abstract: An object recognition method, an object recognition system, and a readable storage medium are provided. The object recognition method is to recognize an object from a first image, and includes: acquiring a first image; calculating depth information of the first image; performing superpixel segmentation on the first image, to obtain a superpixel image; generating three-dimensional image data of the first image according to the depth information and the image data of the superpixel image; and inputting the three-dimensional image data into a depth neural network for object recognition, to obtain a recognition result.

Abstract: A method of processing depth maps comprises receiving (301) images and corresponding depth maps. The depth values of a first depth map of the corresponding depth maps are updated (303) based on depth values of at least a second depth map of the corresponding depth maps. The updating is based on a weighted combination of candidate depth values determined from other maps. A weight for a candidate depth value from the second depth map is determined based on the similarity between a pixel value in the first image corresponding to the depth being updated and a pixel value in a third image at a position determined by projecting the position of the depth value being updated to the third image using the candidate depth value. More consistent depth maps may be generated in this way.

Abstract: The present disclosure relates to systems and methods for image segmentation. The system may include at least one processor that is directed to obtain an image; divide the image into a plurality of image blocks; determine, for each of the plurality of image blocks, a compressed representation of one or more features of the image block; group the plurality of image blocks into at least two different categories based on the plurality of compressed representations; and extract a region of interest from the image based on at least one of the at least two different categories of the plurality of image blocks.

Abstract: A method, apparatus and device for detecting a growth state of a crystalline line of a silicon rod, relating to the technical field of monocrystalline silicon, including in a process of constant-diameter growth of the silicon rod, acquiring a sample image of the silicon rod providing a detection area in the sample image, wherein the detection area overlaps with a crystalline-line growth line of the silicon rod generating a grayscale-value curve of the detection area, and according to the grayscale-value curve of the detection area, determining the growth state of the crystalline line of the silicon rod on the crystalline-line growth line. The method alleviates the affection on the detection of crystalline lines by the fluctuation of the diameter of the silicon rod and the unclarity of the features of the crystalline lines, thereby improving the accuracy and the efficiency of the detection on the crystalline lines.

Abstract: A system for determining blockage of a vehicle camera is configured to apply a partition grid having a plurality of locations to a sequence of images to form a plurality of regions. The system determines at least one spatial feature corresponding to the partition grid and at least one temporal feature corresponding to the partition grid. The system generates a sequence of classifications for each location of the plurality of locations based on the at least one spatial feature, the at least one temporal feature, and reference information. The system applies a smoothing technique to determine a subset of regions that are blocked among the sequence of classifications, and generates an output signal based on the subset of regions. The output may be provided to an output system to wash the camera lens, notify the user or the vehicle of the blockage, or modify image processing.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may determine that a user is in a presence of an information handling system (IHS); determine a digital image of a face of the user; determine an angle of the face of the user with respect to a vertical axis of a camera based at least on the digital image; determine that the face is facing a display associated with the IHS; determine an amount of time, which the user spends looking at the display; determine, via multiple sensors associated with the IHS, a heart rate and a respiratory rate associated with the user; determine that the user should move based at least on the first amount of time, the heart rate, the respiratory rate, and the angle; and display information indicating that the user should move.