Abstract: Systems, methods, and apparatuses are described for processing video. Video content comprising a plurality of frames may be received. A viewing parameters associated with playback of the video content may be determined. One or more of luminance pixel data associated with a frame of the plurality of frames and chrominance pixel data associated with the frame is determined. A quantization matrix associated with the frame may be determined based on the viewing parameter and the one or more of luminance pixel data and chrominance pixel data.

Abstract: A LIDAR sensor for an autonomous vehicle (AV) can include one or more lasers outputting one or more laser beams, one or more non-mechanical optical components to (i) receive the one or more laser beams, (ii) configure a field of view of the LIDAR sensor, and (iii) output modulated frequencies from the one or more laser beams, and one or more photodetectors to detect return signals based on the outputted modulated frequencies from the one or more laser beams.

Abstract: An analytical recognition system is includes a video camera configured to capture video data of a subject and an antenna configured to capture mobile communication device data relating to a mobile communication device of the subject. The system further includes a data analytics module configured to: analyze the video data to determine at least one of a physical attribute or a movement attribute of the subject and generate; generate a first certainty match value based on the at least one of the physical attribute or the movement attribute of the subject; and perform a facial recognition analysis of the subject to obtain facial recognition data.

Abstract: The present invention avoids waste caused by performing both a Secondary Transform and an Adaptive Multiple Core Transform. Provided is a device including: a core transform unit (1521) that can perform an Adaptive Multiple Core Transform on a Coding Tree Unit; and a Secondary Transform unit (1522) that can perform, before the Adaptive Multiple Core Transform, a Secondary Transform on at least any one of sub-blocks included in the Coding Tree Unit. The device omits any of the Adaptive Multiple Core Transform and the Secondary Transform in accordance with at least any of a flag associated with the Adaptive Multiple Core Transform and a flag associated with the Secondary Transform, or in accordance with a size of the Coding Tree Unit.

Abstract: Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.

Abstract: A server system obtains a first video sub-stream comprising a first plurality of images of a scene and obtains a second video sub-stream comprising a second plurality of images of at least a portion of the scene. Images of the second video sub-stream have a higher image resolution or are received at a higher frame rate than images of the first video sub-stream. The first video sub-stream is transmitted to a client device for display. A selection of a region of interest in the scene is received. The server systems locates image data of the selected region of interest from the second plurality of images, and provides the located image data of the selected region of interest to the client device for display.

Abstract: An image processing engine and method of forming a hologram of a target image for projection using data streaming. An input or primary image is sub-sampled using a kernel and the secondary image output used to generate a hologram of the target image. A technique of kernel sub-sampling using a plurality of two or more data streams provides improvements in efficiency, including reduced data storage requirements and increased processing speed.

Abstract: A picture prediction method includes receiving a bitstream, parsing the bitstream to obtain a prediction mode of a current block, when the prediction mode of the current block is a combined intra and inter prediction mode, selecting an execution manner of a triangular prediction unit mode according to a preset policy, determining motion information of the current block according to the execution manner of the triangular prediction unit mode, performing a motion compensation process based on the motion information, to obtain an inter prediction sample, obtaining an intra prediction sample according to the prediction mode of the current block, and combining the inter prediction sample and the intra prediction sample to obtain a prediction picture of the current block.

Abstract: A method of video processing is provided. The method includes: determining, for a conversion between a current video block of a video and a coded representation of the video, a mode of operation of an UMVE mode; and performing the conversion based on the determining, wherein the current video block is coded with an affine merge mode and motion vector differences in the affine UMVE mode, and wherein one or more fields in the coded representation correspond to the mode of operation, and wherein the one or more fields include: a list size field that indicates a size of a base affine merge candidate list for an affine merge mode with prediction offsets that is used by the UMVE mode, or a table field that signals a distance table or a direction table for the affine merge mode with prediction offsets.

Abstract: A laser scanner and a system with a laser scanner for measuring an environment. The laser scanner includes an optical distance measuring device, a support, a beam steering unit rotatably fixed to the support which rotates around a beam axis of rotation. The beam steering unit includes a mirrored surface which deflects radiation used in the optical distance measurement and an angle encoder for recording angle data. The optical distance measurement is performed by a progressive rotation of the beam steering unit about the beam axis of rotation and the continuous emission of a distance measurement radiation, the emission being made through an outlet area arranged in the direction of the mirrored surface on the support, the receiving optics for receiving radiation are arranged on the support, and wherein the outlet area has a lateral offset with respect to the optical axis of the receiving optics.

Abstract: A method of processing an image is proposed, which includes: determining, based on the image, one or more noise templates, wherein each of the one or more noise templates includes noise pixels representing noise contained in the image; calculating one or more first autocovariance values, based on the noise pixels of at least one of the one or more noise templates; based on the one or more first autocovariance values, selecting an entry of a noise model database among database entries which respectively include values of noise model parameters corresponding to a noise model.

Abstract: The present invention relates to a method for performing entropy decoding on a video signal including a current block. The method comprises the steps of: deriving affine coding information and/or affine prediction mode information of a left block and/or an upper block which are adjacent to the current block; determining a context index of a syntax element associated with an affine prediction of the current block on the basis of at least one of the affine coding information and/or the affine prediction mode information of the left block and/or the upper block; and entropy decoding the syntax element associated with the affine prediction of the current block on the basis of the context index.

Abstract: Disclosed are a system and a method for measuring dish size and providing nutritional information using image recognition and augmented reality based on artificial intelligence. The system includes: at least one imaging device acquiring at least one image including at least one dish or at least one food contained in each dish; a service providing apparatus for detecting the at least one dish and the at least one food from the at least one image when the at least one image is received, confirming the name of each detected food on the basis of a learning model, predicting the size of each detected dish, predicting the volume of each detected food using the predicted size of the dish, and generating nutritional information using the predicted volume of each food and pre-stored food information; and a user terminal for visualizing and displaying the nutritional information when the nutritional information is received.

Abstract: A method is provided that includes determining a target picture virtual memory access (VMA) bandwidth rate, wherein the target picture VMA bandwidth rate indicates a maximum VMA bandwidth rate for motion compensation of a picture, and verifying the target picture VMA bandwidth rate for a compressed video bit stream.

Abstract: Techniques for facilitating shutter and light signal synchronization systems and methods are provided. In one example, a system includes a vehicle. The vehicle includes a light emitting device configured to emit a light signal. The vehicle further includes a logic device configured to transmit data associated with the light signal. The system further includes a wearable apparatus. The wearable apparatus includes a shutter device configured to synchronize with the light signal based on the data and process the light signal according to the synchronization. Related methods and devices are also provided.

Abstract: A method, system and computer program product for reducing learning time for a newly installed camera is disclosed. The method includes generating a new unusual activity model for the newly installed camera, based on portion(s) of existing and established unusual activity model(s) built for different older camera(s), where the existing and established unusual activity model(s) relate to at least one same static object appearing within Fields Of Views (FOVs) of the new and older cameras.

Abstract: An image capturing apparatus and a method for depth of filed (DOF) adjustment in images based on time of flight (TOF) depth maps is provided. The image capturing apparatus includes an image sensor and circuitry. The circuitry generates a TOF depth map of a scene that includes a plurality of objects. The TOF depth map includes information associated with distances between the image sensor and surfaces of the plurality of objects. The circuitry divides the TOF depth map into a plurality of regions that corresponds to at least one object of the plurality of objects. The circuitry determines a region of interest from the plurality of regions and adjusts the DOF of the at least one object associated with the determined region of interest. The circuitry further controls the image sensor to capture an image of the scene based on the adjusted DOF.

Abstract: Structured light is projected onto an object, and an image of the object as illuminated by the projected structured light is captured. Reference object points are identified within the captured image, and the structured light projected onto the object is modified based on the identified reference object points. An additional image of the object as illuminated by the modified projected structured light is captured, and additional reference object points are identified within the captured additional image.

Abstract: A microscope system 1 includes an eyepiece 104, an objective 102 that guides light from a sample to the eyepiece 104, and a tube lens 103 that is disposed on a light path between the eyepiece 104 and the objective 102 and forms an optical image of the sample on the basis of light therefrom. The microscope system 1 further includes a projection apparatus 133 that projects first and second projection images onto an image plane on which the optical image is formed, in a manner such that the first and second projection images are capable of being distinguished from each other. The first projection image is based on an analysis result provided by a computer for the digital image data of the sample. The second projection image is based on an input operation performed by a user and includes at least input information provided by the user.

Abstract: There is provided an image processing apparatus and a method capable of achieving reduction of a drop of coding efficiency (improvement of coding efficiency). Coded data is decoded to generate coefficient data. An inverse orthogonal transform is performed for the generated coefficient data according to an inverse orthogonal transform type controlled on the basis of a coding parameter. For example, the present disclosure is applicable to an image processing apparatus, an image coding apparatus, an image decoding apparatus, or the like.