Abstract: Method involving: providing an object in the video that at least partially and at least occasionally is presented in frames of a video; detecting the object in the video, wherein said detection comprises detecting feature reference points of the object; tracking the detected object in the video, wherein the tracking comprises creating a mesh that is based on the detected feature reference points of the object and aligning the mesh to the object in each frame; generating a first set of node points on the created mesh based on a request for changing proportions; generating a second set of node points based on the first set of node points; and transforming the frames of the video in such way that the object's proportions are transformed in accordance with the second set of the node points using the mesh.

Abstract: A system and method for generating high resolution images using a plenoptic camera, is provided. In one embodiment, the comprises capturing a first set of images in a first unexcited state of operation by using a birefringent medium disposed between a main lens and an array of lenses having a plurality of apertures. Each pixel of the first set of images is then mapped to a first set of apertures. The first unexcited state is then caused to become a second excited state by applying a voltage across said birefringent medium. A second set of images are captured in the second excited state and a second set of pixels of the second image is mapped to a second set of apertures. A value is calculated for each first and second set of images and the value associated with said first set of images is subtracted from at least two times the value calculated from said second set of image.

Abstract: Techniques of color image processing involve performing a transformation for each color channel that mixes intensity values from other channels to produce a new intensity value for that channel. The new intensity values, representing the effect of overlapped response spectra of the S, M, and L cones, then provide values of the sensitivities of the photoreceptors of each of the cones. These values of the sensitivities form the basis of more accurate color image processing. For example, compression ratios of gamma-compressed color images may be increased when more the sensitivities are more accurate.

Abstract: In an image processing apparatus, an image obtaining unit obtains, from a vehicular camera, an image captured by the vehicular camera based on a predetermined imaging condition. An image processing unit executes an image-processing task of the image. A histogram generation unit generates a histogram based on the luminance values of the pixels included in the road-surface region in the image. The histogram graphically represents a frequency of each of the luminance values of the pixels included in the road-surface region in the image. A histogram determination unit determines whether the histogram has first and second separate crests. A change unit changes, upon determination that the histogram has first and second separate crests, at least one of 1. The imaging condition of the vehicular camera 2. The image-processing task to be executed by the image processing unit.

Abstract: A head-mounted display, a display control method, and a program that facilitate a user to understand proximity between the user and an object around the user are provided. A display block (36) is arranged in front of the eyes of the user wearing a HMD (12). In accordance with proximity between the user and an object around the user, the HMD (12) controls the display block (36) so as to have the user visually recognize a forward direction of the display block (36).

Abstract: A method for guiding resection of local tissue from a patient includes generating at least one image of the patient, automatically determining a plurality of surgical guidance cues indicating three-dimensional spatial properties associated with the local tissue, and generating a visualization of the surgical guidance cues relative to the surface. A system for generating surgical guidance cues for resection of a local tissue from a patient includes a location module for processing at least one image of the patient to determine three-dimensional spatial properties of the local tissue, and a surgical cue generator for generating the surgical guidance cues based upon the three-dimensional spatial properties. A patient-specific locator form for guiding resection of local tissue from a patient includes a locator form surface matching surface of the patient, and a plurality of features indicating a plurality of surgical guidance cues, respectively.

Abstract: Systems, apparatuses and methods may provide for technology that partitions a high dynamic range (HDR) image into a plurality of regions and determines, on a per region basis, a luminance level of the HDR image. Additionally, the technology may select, on the per image basis, a encoding amount for each region in the plurality of regions based on the luminance level.

Abstract: A computer includes a processor and a memory, the memory storing instructions executable by the processor to apply a transform function to a plurality of images from a real-world dataset to generate a plurality of feature vectors, to apply a subspace generation algorithm to generate basis vectors of a subspace, and to project a simulated image onto the subspace to generate a realistic synthetic image.

Abstract: Techniques are provided that include obtaining a vocabulary including a set of content indices that reference corresponding cells in a descriptor space based on an input set of descriptors. A plurality of local features of an image are identified based on the vocabulary, the local features being represented by a plurality of local descriptors. An associated visual word in the vocabulary is determined for each of the plurality of local descriptors. A plurality of global signatures for the image are generated based on the associated visual words, wherein some of the plurality of global signatures are generated using local descriptors corresponding to different cropped versions of the image, two or more of the different cropped versions of the image being centered at a same pixel location of the image, and an image recognition search is facilitated using the plurality of global signatures to search a document image dataset.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for machine learning. One of the methods includes receiving a document having a plurality of first text strings; extracting the plurality of first text strings from the document; providing the extracted plurality of first text strings to a first machine learning model, wherein the first machine learning model is trained to output a numerical vector representation for each input first text string; providing the output vector representations from the first machine learning model to a second machine learning model, wherein the second machine learning model is trained to output a second text string for each input vector representation; and processing the second text strings to generate an output.

Abstract: There is provided a recognition system adaptable to a portable device or a wearable device. The recognition system senses a body heat using a thermal sensor, and performs functions such as the living body recognition, image denoising and body temperature prompting according to detected results.

Abstract: A map construction method, an electronic device and a readable storage medium are disclosed. The map construction method includes: obtaining three-dimensional point cloud data corresponding to observed objects in current target frame data, the observed objects including a feature object and a non-feature object; obtaining a feature parameter corresponding to the feature object based on three-dimensional point cloud data corresponding to the feature object, the feature parameter being used to indicate a position and a size of the feature object; and adjusting a point cloud density of three-dimensional point cloud data corresponding to the non-feature object to a preset value, to construct a map according to the feature parameter and the three-dimensional point cloud data of which the point cloud density is adjusted.

Abstract: Systems and methods of identifying unknown video content are described. An example method may include receiving a first fingerprint and a second fingerprint. The first fingerprint may be a color-based fingerprint derived from colors in a portion of the unknown video content, and the second fingerprint may be at least partially based on a feature other than the colors of the unknown video content. A reference database of reference fingerprints may then be queried using one of the first fingerprint or the second fingerprint to obtain a candidate group of fingerprints. The candidate group of fingerprints may then be queried using the other of the first fingerprint and the second fingerprint to identify at least one query fingerprint. The unknown video content may then be identified using the at least one query fingerprint.

Abstract: An image processing technique is presented using a hierarchical image model. The technique may be used as a precursor to subsequent image processing, to fix detected images in a post processing stage or as a segmentation or classification stage. The techniques may also be applied to super resolution. In a first layer of the hierarchical image model, each observed pixel of the image has a representation allocated to one or more input node. A set of the input nodes are assigned to a hidden node of a second layer, and a duplicate set of input nodes of the first layer is assigned to a duplicate of the hidden node in the second layer. In this way, a dense latent tree is formed in which a subtree is duplicated. Variables are assigned to the input nodes, the hidden node and the duplicate nodes and recurringly modified to process the image. Belief propagation messages may be utilised to recursively modify the variables. An image processing system using the method is described.

Abstract: Disclosed is an image data compression method including determining whether image data can be compressed by a target compression ratio using one of at least one lossless compression scheme for compressing image data, when the image data can be compressed by the target compression ratio using the one of the at least one lossless compression scheme, encoding the image data using the one of the at least one lossless compression scheme, and when the image data cannot be compressed by the target compression ratio using the one of the at least one lossless compression scheme, encoding the image data by the target compression ratio using one of at least one lossy compression scheme.

Abstract: Embodiments of the present disclosure relate to object detection in an image. In an embodiment, a computer-implemented method is disclosed. According to the method, image data representing a scene is obtained and sound distribution information related to the scene is obtained. A detection strategy to be applied in object detection is determined based on the sound distribution information. The object detection is performed on the image data by applying the detection strategy. In other embodiments, a system and a computer program product are disclosed.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: An object is tracked in images of the space. A unique identification is assigned to the object and the uniquely identified object may then be located within the space based on the tracking of the object, without having to again uniquely identify the object.

Abstract: A method of automatically orienting symmetric and asymmetric produce items, such as apples for example, is provided. Individual items of produce are manipulated by a programmable manipulator within the view of one or more depth imaging cameras. Digital three dimensional characterizations of the surface of the produce items are generated by the depth imaging camera or cameras and are utilized by a computer connected to the depth imaging camera or cameras to locate the stem and blossom of each produce item. Asymmetric produce items, such as apples with dropped shoulders as well as symmetric produce items can be properly oriented and processed automatically.