Abstract: A volume measuring apparatus is disclosed and includes a body having a working part and a holding part extended downward from the bottom of the working part, a processor arranged in the body, a first camera, a second camera, and a barcode capturing unit arranged on a front end of the working part, a first button arranged on one side of the holding part, and a second button arranged on a top of the working part. The first button and the second button are different types of button. By respectively operating the first button and the second button, the processor is controlled to perform a measuring action of the volume of a target box or to perform a decoding action of a target barcode based on the image captured by at least one of the first camera, the second camera, and the barcode capturing unit.

Abstract: There is provided a method for encoding and decoding a signal. The input signal (1000) is processed by at least converting the input signal (1000) from a high-dynamic range—HDR-signal to a standard dynamic range—SDR-signal, to produce a first processed signal. The first processed signal is encoded by a first encoding module (1004) to generate a first encoded signal (1012). The first encoded signal (1012) is decoded to generate a first decoded signal. The first decoded signal is processed together with the first processed signal by a second encoding module (1006) to generate a second encoded signal (1014). The second encoded signal (1014) is decoded and the result is combined with the first decoded signal (1012) to generate a second decoded signal. The second decoded signal is processed at least by converting the second decoded signal from a SDR signal to a HDR signal, to produce a second processed signal.

Abstract: Devices, systems and methods for video processing are described. In an exemplary aspect, a method for video processing includes encoding a video unit of a video as an encoded video unit; generating reconstruction samples from the encoded video unit; performing a clipping operation on the reconstruction samples, wherein a clipping parameter used in the clipping operation is a function of a clipping index and a bit-depth of the reconstruction samples or a bit-depth of samples of the video unit; applying a non-linear adaptive loop filter to an output of the clipping operation; and generating a coded representation of the video using the encoded video unit.

Abstract: An imaging apparatus includes: an image sensor; a signal processing unit repeatedly performing processing different from each other in a given number of sequential frames to imaging signals obtained by the image sensor to thereby obtain image data of respective frame; and an image data output unit sequentially outputting the image data of respective frames.

Abstract: An image decoding method, a decoder and a storage medium are porovided. The method includes: receiving code stream data, and parsing the code stream data to obtain a coding tree unit corresponding to the code stream data; parsing an i-th node of i-th layer corresponding to the coding tree unit to obtain i-th state parameter and i-th flag parameter corresponding to the i-th node; performing detection processing on the i-th node according to the i-th state parameter and the i-th flag parameter to obtain an i-th detection result; acquiring a (i+1)th node of a (i+1)th layer corresponding to the coding tree unit; continuing to perform detection processing on the (i+1)th node, and traversing all the nodes corresponding to the coding tree unit until all the coding unit data corresponding to the coding tree unit is obtained; and generating a decoded image corresponding to the code stream data.

Abstract: An image acquisition system includes: a first narrowband light source that emits first narrowband light for exciting a luminescent agent that exists in an observation target and emits light having a wavelength belonging to a visible light wavelength band; a second narrowband light source that emits second narrowband light in a wavelength band of ±30 nm of a peak light emission wavelength of the luminescent agent; a broadband light source that emits broadband light for illuminating the observation target; a first image sensor on which an image of light in a light emission wavelength band including a wavelength corresponding to light emitted from the luminescent agent is formed; and a second image sensor including one or more image sensors on which an image of light in a wavelength band other than the light emission wavelength band is formed.

Abstract: A method of wheel encoder to camera calibration, including receiving a LiDAR (Light Detection and Ranging) signal, receiving a camera signal, receiving a wheel encoder signal, calibrating the camera signal to the LiDAR signal, calibrating the wheel encoder signal to the LiDAR signal and calibrating the camera signal to the wheel encoder signal based on the calibration of the camera signal to the LiDAR signal and the wheel encoder signal to the LiDAR signal.

Abstract: Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. An apparatus for video decoding includes processing circuitry that decodes prediction information for a current block in a current coded picture. The prediction information indicates an intra block copy (IBC) prediction mode used for the current block, an index to select a block vector predictor candidate from a block vector predictor candidate list for the current block, and whether a non-zero residue exists for the current block. The processing circuitry constructs the block vector predictor candidate list for the current block in a same sequence of candidates, no matter whether the no-zero residue exists for the current block. The processing circuitry selects a block vector predictor candidate from the constructed block vector predictor candidate list based on the index indicated in the prediction information and reconstructs the current block according to the selected block vector predictor candidate.

Abstract: Various embodiments concern a system for monitoring a patient in a bed, the system comprising a camera, a user interface comprising a screen, and a computing system. The computing system can be configured to monitor, with the camera, for motion within each of a plurality of zones, the plurality of zones comprising a one or more inner zones extending adjacent along the bed, one or more outer zones extending adjacent along the one or more inner zones, and one or more end zones. Motion within the inner zones can trigger a fall alert while motion within the outer or end zones can suspend one or more functions to prevent the fall alert from being issued. The end zones can comprise a bottom zone and one or more top zones.

Abstract: An information processing device includes: an acquisition unit that acquires feature information of a target depicted in images; a storage unit that stores registration information containing feature information of registered targets; and a distinction unit that distinguishes, on a basis of a result of identification of the feature information acquired by the acquisition unit and the feature information contained in the registration information, one registered target of the registered targets, the one registered target corresponding to the target in the images. The registration information contains zip codes of sites relating to the registered targets. The distinction unit identifies a zip code of a site relating to the target in the images and zip codes contained in registration information with each other, and distinguishes one registered target corresponding to the target in the images using the result of identification of the feature information and using the identification of the zip codes.

Abstract: A vehicle analysis environment includes one or more display screens, such as a display screen wall or an array of display screens. While a vehicle is in the vehicle analysis environment, a vehicle analysis system renders and displays one or more vehicle sensor calibration targets and/or one or more simulated events on the one or more display screens. Vehicle sensors of the vehicle capture sensor data while in the vehicle analysis environment. The sensor data depict the vehicle sensor calibration targets and/or the simulated events that are displayed on the one or more display screens. The vehicle can output actions based on the simulated event and/or can calibrate its vehicle sensors based on the vehicle sensor calibration targets.

Abstract: A camera system and method are disclosed. The camera includes a memory, a camera, and a processor. The memory stores an adaptively subsampled look-up table. The adaptively subsampled look-up includes varying levels of subsampling across the adaptively subsampled look-up table. The camera captures an image, and the captured image is distorted based on varying distortions within an optical system of the camera. The processor receives the captured image from the camera, corrects the distorted captured image based on the adaptively subsampled look-up table to create a correct image, provides the corrected image, and executes a safety feature based on the corrected image.

Abstract: An encoder is configured to compress spatial information for points included in a three-dimensional (3D) volumetric content representation using an octree, predictive tree, or other geometric compression technique. For points of the 3D volumetric content that are spatially located as same or similar locations in 3D space, such duplicated points, may be signaled using a duplicate point count. The duplicate point count may be used instead of explicitly signaling (duplicated) spatial information in the predictive tree for the duplicated points, as an example. Similarly a decoder is configured to generate a reconstructed three-dimensional representation of the volumetric content that includes the duplicate points, wherein the reconstructed 3D representation is generated from a bit stream including one or more duplicate point counts.

Abstract: A method for aligning a calibration device for calibrating a vehicle environmental sensor of a vehicle, and a device for carrying out such a method. The method includes: measuring a temporal curve of at least one measurement point using the camera, determining the geometrical driving axis from the temporal curve of the at least one measurement point, measuring a first and a second lateral distance value of the vehicle using the distance sensors at a measurement time, determining a center of a vehicle axle at the measurement time on the basis of the ascertained lateral distance values, correlating the geometrical driving axis to the center of the vehicle axle at the measurement time and determining an axially centric geometrical driving axis, and aligning the calibration device in correspondence to the ascertained axially centric geometrical driving axis.

Abstract: A slide rack determination system for a digital slide scanning apparatus. In an embodiment, a motor drives a slide rack at a known rate toward an engagement surface. The elapsed time until engagement may be used to detect the presence or absence of the slide rack and/or the height of the slide rack. In addition, one or more sensors may detect one or more features of the slide rack, and these feature(s) may be used to determine the presence or absence of a slide rack, whether usage of the slide rack is supported or unsupported by the digital slide scanning apparatus, the orientation of the slide rack, and/or the manufacturer and/or model of the slide rack.

Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising predicting a viewpoint within a volumetric video based on a movement input provided by a viewer, resulting in a predicted viewpoint at a future time, retrieving a cell occupancy bitmap for a point cloud of the volumetric video for the future time, determining visible cells based on the cell occupancy bitmap and the predicted viewpoint, where the visible cells are not obscured by points in other cells, and retrieving points of the point cloud that are within the visible cells prior to the future time.

Abstract: A method for decoding an image, according to the present invention, can comprise the steps of: drawing out a vector predictor of a block vector for indicating a reference block with respect to a current block to be predicted within a current picture; drawing out the block vector on the basis of the vector predictor and a vector differential value corresponding to a different value of the block vector and the vector predictor; and generating a prediction block with respect to the current block on the basis of the block vector.

Abstract: Disclosed are an intra-prediction mode-based image processing method and a device therefor. Particularly, a method for processing an image on the basis of an intra-prediction mode may comprise the steps of: configuring a reference sample to be used for prediction of a current block on the basis of width information and height information of the current block when the current block is a non-square block; deriving an intra-prediction mode of the current block; and generating a prediction sample of the current block by using the reference sample on the basis of the intra-prediction mode of the current block.

Abstract: Camera head apparatus, systems, and methods for providing wide angle/panoramic images and/or video of the interior of pipes or other cavities using multiple imaging and illumination modules are disclosed.

Abstract: A method for calibrating a vehicular camera of a vehicular vision system includes placing a target with a first portion having a first geometric pattern and a second portion having a second geometric pattern within the field of view of the vehicular camera, and capturing image data with the camera representative of the field of view of the vehicular camera. Two edges of both portions of the target are detected, and edge pixels of the detected edges are determined. First and second vanishing points of the target in the captured image data are determined based on the determined edge pixels of the respective first and second portions of the target. Camera orientation is determined based on location of the determined first vanishing point relative to location of the determined second vanishing point. The vehicular camera is calibrated based on the determined camera orientation.