Abstract: A remote image transmission system, a display apparatus, and a guide displaying method of a display apparatus are provided. The remote image transmission system includes: an image capturing apparatus including a plurality of image pickup devices that are spaced from each other, the image capturing apparatus being configured to transmit, to a display apparatus, a plurality of images which are captured by the plurality of image pickup devices; and a display apparatus configured to generate a guide object indicating physical information of a captured object by using the plurality of received images, and to display the generated guide object and at least one of the plurality of images.

Abstract: Camera settings are managed. A candidate subject for capture by a camera is detected. The detection is based on historical profile data related to a user of the camera. One or more adjustments of the camera are identified for capture of the candidate subject. The one or more adjustments are identified based on the detected candidate subject. A proper capture action is performed based on the identified adjustments.

Abstract: In computer vision systems that need to decode machine-readable indicia from captured imagery, it is critical to select imaging parameters (e.g., exposure interval, exposure aperture, camera gain, intensity and duration of supplemental illumination) that best allow detection of subtle features from imagery. In illustrative embodiments, a Shannon entropy metric or a KL divergence metric is used to guide selection of an optimal set of imaging parameters. In accordance with other aspects of the technology, different strategies identify which spatial locations within captured imagery should be successively examined for machine readable indicia, in order to have a greatest likelihood of success, within a smallest interval of time. A great variety of other features and arrangements are also detailed.

Abstract: The disclosure relates to an image processing apparatus for selecting a plurality of depth information values for a subset of currently processed fragments of a set of currently processed fragments of a currently processed digital image. The image processing apparatus includes a non-transitory memory storage comprising instructions and one or more hardware processors in communication with the memory storage. The one or more hardware processors execute the instructions to: process the currently processed fragments of the set of currently processed fragments in parallel; and process the currently processed fragments of the subset of currently processed fragments in parallel.

Abstract: Embodiments disclosed herein involve techniques for automatically retouching photos. A neural network is trained to generate a skin quality map from an input photo. The input photo is separated into high and low frequency layers which are separately processed. A high frequency path automatically retouches the high frequency layer using a neural network that accepts the skin quality map as an input. A low frequency path automatically retouches the low frequency layer using a color transformation generated by a second neural network and the skin quality map. The retouched high and low frequency layers are combined to generate the final output. In some embodiments, a training set for any or all of the networks is enhanced by applying a modification to an original image from a pair of retouched photos in the training set to improve the resulting performance of trained networks over different input conditions.

Abstract: A method for outputting information corresponding to an object includes identifying a shape of the object, receiving an image of a label corresponding to the object, generating a three-dimensional model of the object to which the image of the label is virtually attached based on the identified shape of the object and the image of the label, generating a plurality of pieces of two-dimensional image data corresponding to the three-dimensional model of the object, the plurality of pieces of two-dimensional image data being generated by changing a virtual capturing position for capturing the three-dimensional model of the object, comparing input image data to the plurality of pieces of two-dimensional image data and outputting the information corresponding to the object based on a positive comparison between the input image data and at least one of the plurality of pieces of two-dimensional image data.

Abstract: Images of items are evaluated. A first image of the item, having a view of two or more of its surfaces, is captured at a first time. A measurement of at least one dimension of one or more of the surfaces is computed and stored. A second image of the item, having a view of at least one of the two or more surfaces, is captured at a second time, subsequent to the first time. A measurement of the dimension is then computed and compared to the stored first measurement. The computed measurement is evaluated based on the comparison.

Abstract: An apparatus includes a first acquisition unit configured to, with a viewpoint set to a position of an object, acquire a plurality of environment maps for each position of light sources, the environment maps being obtained by imaging a surrounding environment from the viewpoint, a second acquisition unit configured to acquire a plurality of captured images for each position of the light sources, the captured images being obtained by imaging from a plurality of directions the object irradiated with light by the light sources, and a determination unit configured to determine reflection characteristics of the object based on the environment maps and the plurality of captured images.

Abstract: Aspects described herein apply machine learning techniques for image recognition and classification to the processing of topographic imagery, in order to permit more accurate and detailed topographic representations of an area to be obtained. In particular, in one embodiment a machine learning system is trained with existing topographic imagery and corresponding topographic data relating to a particular area, so that the machine learning system is then able to relate actual physical topographical features to their topographic representations in existing data. Having been so trained, the machine learning system may then be used to process topographic imagery data of the same area to determine new topographic details thereof for incorporation into the topographic data.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for improved patch validity testing for patch-based synthesis applications using similarity transforms. The improved patch validity tests are used to validate (or invalidate) candidate patches as valid patches falling within a sampling region of a source image. The improved patch validity tests include a hole dilation test for patch validity, a no-dilation test for patch invalidity, and a comprehensive pixel test for patch invalidity. A fringe test for range invalidity can be used to identify pixels with an invalid range and invalidate corresponding candidate patches. The fringe test for range invalidity can be performed as a precursor to any or all of the improved patch validity tests. In this manner, validated candidate patches are used to automatically reconstruct a target image.

Abstract: According to some aspects, an image processing apparatus is provided. The image processing apparatus includes circuitry configured to receive at least two images of a biological sample and determine motion information for a plurality of regions of the at least two images. The motion information corresponds to motion of the biological sample. The circuitry is further configured to generate a graphical representation of at least two characteristic amounts. The at least two characteristic amounts correspond to a region of the plurality of regions and one characteristic amount of the at least two characteristic amounts is indicative of the motion information.

Abstract: Techniques detecting usage of copyrighted video content using object recognition are provided. In one example, a computer-implemented method comprises determining, by a system operatively coupled to a processor, digest information for a video, wherein the digest information comprises objects appearing in the video and respective times at which the objects appear in the video. The method further comprises comparing, by the system, the digest information with reference digest information for reference videos, wherein the reference digest information identifies reference objects appearing in the reference videos and respective reference times at which the reference objects appear in the reference videos. The method further comprises determining, by the system, whether the video comprises content included in one or more of the reference videos based on a degree of similarity between the digest information and reference digest information associated with one or more of the reference videos.

Abstract: A method for identifying social relation of persons in an image, including: generating face regions for faces of the persons in the image; determining at least one spatial cue for each of the faces; extracting features related to social relation for each face from the face regions; determining a shared facial feature from the extracted features and the determined spatial cue, the determined feature being shared by multiple the social relation inferences; and predicting the social relation of the persons from the shared facial feature.

Abstract: Devices, systems and methods are disclosed for performing image processing at a camera-level. For example, a camera service may run on top of a camera hardware abstraction layer (HAL) and may be configured to perform image processing such as applying a blurring algorithm, applying a color filter and/or other video effects. An application may pass metadata to the camera service via an application programming interface (API) and the camera service may use the metadata to determine parameters for the image processing. The camera service may apply the blurring algorithm for a first period of time before transitioning to unblurred image data over a second period of time.

Abstract: Disclosed is a facial verification apparatus and method. The facial verification apparatus is configured to detect a face area of a user from an obtained input image, generate a plurality of image patches, differently including respective portions of the detected face area, based on a consideration of an image patch set determination criterion with respect to the detected face area, extract a feature value corresponding to a face of the user based on an image patch set including the generated plurality of image patches, determine whether a facial verification is successful based on the extracted feature value, and indicate a result of the determination of whether the facial verification is successful.

Abstract: The image inspection device includes: a first extraction unit configured to repeatedly execute processing for moving a predetermined region by a predetermined distance on an inspection target image to extract an image of the predetermined region after movement as a first determination image until a predetermined first ratio of the inspection target image is included in a plurality of first determination images, and a second extraction unit configured to repeatedly execute processing for moving a predetermined region by a distance smaller than the predetermined distance on an image in the inspection target image including a first determination image where a determined degree satisfies a predetermined condition to extract an image of the predetermined region after movement as a second determination image until a predetermined second ratio of the image in the inspection target image including a first determination image is included in a plurality of second determination images.

Abstract: A system for determining a state of a driver includes a face tracking device configured to detect coordinates and a direction vector of a face at intervals of a sampling time from a face image of the driver, an event detecting device configured to detect valid behavior of a vehicle as an event, and a determination device configured to determine an impaired state of the driver based on a reflex response time of the driver when the event is detected by the event detecting device.

Abstract: There is provided with an image processing apparatus. A determination unit determines color information of an object present in an object image from a virtual viewpoint. The color information of the object is determined by combining color information of the object in a captured image obtained by one or more image capturing apparatus selected based on position and orientation information of the virtual viewpoint, position and orientation information of the image capturing apparatuses, and position information of the object, by using a weight corresponding to an image capturing direction of the one or more image capturing apparatus and a position of the object in a field of view of the one or more image capturing apparatus.

Abstract: An image processing apparatus includes a core configured to perform a fast Fourier transformation (FFT) operation on the image data, a memory configured to store data that is output by the core, and a controller configured to control the core to perform the FFT operation on the image data. The core is resettable based on an amount of the image data.

Abstract: Presented herein are systems, methods, and apparatus that analyze molecular imprints for detecting cancerous cells. Embodiments of the present disclosure include systems, methods, and apparatus that analyze metabolic imprints of cells for cancer detection. In certain embodiments, the methods/systems comprise extracting thermal and thermodynamic quantities and properties from the molecular imprints. The thermal/thermodynamic quantities and/or further-processed quantities can be mapped on a universal cancer diagnostic scale for disease stratification, thereby providing/determining a normality status of the subject cells.