Abstract: The present application provides an object tracking method. The object tracking method includes obtaining an image of an area in front of a vehicle; dividing the image of the area in the front of the vehicle into a plurality of sub-images; determining a plurality of first sub-images that satisfy a plurality of threshold conditions out of the plurality of sub-images; selecting a plurality of target sub-images out of the plurality of first sub-images, at least one of the plurality of first sub-images is not selected as one of the plurality of target sub-images; and recognizing a target object in one of the plurality of target sub-images.

Abstract: The present disclosure provides an image processing method, device and apparatus, and a computer-readable storage medium. The image processing method includes: obtaining an image and detecting multiple targets in the image; obtaining categories of multiple detected targets and first parameters of a detection frame corresponding to each detected target, and ranking all detected targets according to the first parameters in a descending order to obtain a dataset; obtaining a target with a highest first parameter in the dataset as a first detected target, and detecting whether the first parameter of a first detection frame corresponding to the first detected target satisfies a preset category condition of a category to which the first detected target belongs; detecting whether the first detection frame corresponding to the first detected target overlaps with a detection frame corresponding to a respective one of the plurality of detected targets except the first detected target.

Abstract: A control circuit includes: a power supply module, arranged to generate an output power to control an operation mode of a lighting device according to a control signal and a supply power; a switching module, coupled to the supply power, for selectively generating a first voltage signal of the supply power; and a signal controlling module, coupled between the switching module and the power supply module, for generating the control signal according to the first voltage signal.

Abstract: An intelligent power adaptor includes a housing, a circuit board, a holder and a detachable intelligent current adaptor. The housing has an internal space and an insertion through hole. The circuit board is disposed within the internal space. The circuit board includes a plurality of first connecting terminals. The holder is coupled to the circuit board. Also, the holder is disposed above the circuit board and within the internal space. In addition, the holder includes an opening for encompassing the plurality of first connecting terminals. The detachable intelligent current adaptor is detachably coupled to the holder via the opening and externally coupled to the housing via the insertion through hole. The detachable intelligent current adaptor includes a plurality of second connecting terminals that are detachably docked with and electrically coupled to the plurality of first connecting terminals in one-by-one correspondence.

Abstract: A method for stabilizing rice bran with complex enzyme involving enzymatic hydrolysis combined with thermal processing to stabilize rice bran, includes compounding at least one of glycosyl hydrolases such as cellulase, hemicellulase and alpha amylase into a complex enzyme solution, and performing enzymatic hydrolysis on the rice bran with the complex enzyme solution, and after enzymatic hydrolysis, performing thermal processing and inactivating enzyme treatment on rice bran using the moist-heat method, microwave method and/or extrusion expansion method, to prepare the stabilized rice bran. From the perspective of reducing bound lipase from rice bran, the glycosyl hydrolase is used to catalyze conversion of bound lipase in rice bran into free lipase, thereby effectively improving inactivation efficiency of rice bran lipase. The rice bran prepared using the method has characteristics of low residual activity of lipase and long shelf life, and may be directly applied to industries such as food and cosmetics.

Abstract: Aspects of the subject disclosure may include, for example, a machine-readable storage medium, including executable instructions that, when executed by a processing system including a processor, facilitate performance of operations that include assuming control of a video content transfer between a video server and a video client for HTTP traffic responsive to determining the HTTP traffic is for video content, generating a video transfer rate selection and a video transfer resolution selection for a requested video chunk of a time slot of the video content, generating an optimized manifest file for the requested video chunk, and publishing the optimized manifest file to the video client, wherein the video client request the requested video chunk from the video server based on the optimized manifest. Other embodiments are disclosed.

Abstract: A commodity detection terminal is disclosed, the commodity detection terminal includes: an image segmentation unit configured to obtain position information of each grid of a goods shelf in an image of the goods shelf based on a first image, which is an image of the goods shelf not placed with commodities; a detector unit configured to obtain a current grid where each commodity is located and a current quantity of each commodity based on a second image, which is a current image of the goods shelf placed with commodities; and a determination unit configured to compare the current grid and the current quantity with a preset grid and a preset quantity of the each commodity, so as to determine whether a status of each commodity satisfies a preset condition. A commodity detection method, an intelligent goods shelf system, a computer device, and a readable medium are also disclosed.

Abstract: Embodiments of the disclosure provide an object detection method and device. The object detection method includes: extracting features of an image; classifying the image by each level of classifiers of a cascade classifier according to the features of the image, and calculating a classification score of the image in each level of the classifiers of the cascade classifier according to a classification result; and calculating, according to the classification score, a cascade score of the image in a corresponding level of the cascade classifier, comparing the cascade score in the corresponding level with a cascade threshold of the corresponding level, and judging the presence of an object in the image according to a comparison result.

Abstract: The embodiments of the present disclosure disclose a method and apparatus for extracting an edge of an object in a depth image, a storage medium, and a computer device, to provide a solution which is simple to implement and accurate in edge extraction. The method for extracting an edge of an object in a depth image includes: calculating at least two sets of edge pixels of a first depth image using at least two edge detection algorithms; and acquiring a final set of edge pixels by combining the at least two sets of edge pixels. The solution according to the embodiments of the present disclosure is simple to implement, and may obtain a more accurate set of edge pixels, thereby obtaining an accurate pixel-level segmentation result.

Abstract: A method for tracking an at least partially occluded object. The method includes recognizing a non-occluded portion of the at least partially occluded object in an input image; generating a simulated image of the at least partially occluded object based on features of the non-occluded portion extracted from the input image; determining first coordinates of the at least partially occluded object in a first coordinate system; and converting the first coordinates of the at least partially occluded object in the first coordinate system into second coordinates in a second coordinate system defined in a display apparatus.

Abstract: The present application provides a model training method and apparatus, an electronic device and a readable storage medium. The model training method of a pedestrian re-identification network, includes: determining a current weight matrix for multiple identification objects according to a current training result of a neural network model; calculating a difficulty vector corresponding to the multiple identification objects according to the current weight matrix; and, selecting next training samples of the multiple identification objects for a next training according to the difficulty vector.

Abstract: Aspects of the subject disclosure may include, for example, a machine-readable storage medium, including executable instructions that, when executed by a processing system including a processor, facilitate performance of operations that include assuming control of a video content transfer between a video server and a video client for HTTP traffic responsive to determining the HTTP traffic is for video content, generating a video transfer rate selection and a video transfer resolution selection for a requested video chunk of a time slot of the video content, generating an optimized manifest file for the requested video chunk, and publishing the optimized manifest file to the video client, wherein the video client request the requested video chunk from the video server based on the optimized manifest. Other embodiments are disclosed.

Abstract: The present disclosure provides a line segment detection method, apparatus, device, and a computer-readable storage medium. Said method includes: extracting image features of an image to be processed, the image features including an image gradient angle and an image gradient amplitude; determining a plurality of seed points based on the extracted image features; for each seed point of the plurality of seed points, determining a current connected region of respective seed point according to a region growth rule, wherein the region growth rule needs to satisfy both a gradient amplitude growth rule and a gradient angle growth rule simultaneously; and performing line segment fitting on line segments within the current connected region of respective seed point.

Abstract: A method of encoding a watermark into a digital image is provided. The method includes partitioning an image into a plurality of blocks of a same size; accumulating the plurality of blocks of the same size into a single block image; performing a Fourier transformation on the single block image to obtain a two-dimensional Fourier spectrum defined by Fourier coefficients at different positions of a Fourier domain; inserting a watermark into a frequency domain of the two-dimensional Fourier spectrum by modifying the two-dimensional Fourier spectrum as a function of watermarking coefficients in the watermark, to obtain a modified Fourier spectrum; performing an inverse Fourier transformation on the modified Fourier spectrum to obtain a watermarked image; copying the watermarked image horizontally and vertically into a plurality of copied watermarked images; and splicing the plurality of copied watermarked images into a reconstituted watermark image.

Abstract: A computer-implemented method of detecting a foreign object on a background object in an image is provided. The computer-implemented method includes extracting image features of the image based on image characteristics of the background object and a suspected foreign object; detecting a salient region in the image based on a human visual attention model; generating a salient region mask based on detection of the salient region; obtaining the image features in a region surrounded by the salient region mask; perforating feature combination and feature vector length normalization on the image features of the region surrounded by the salient region mask to generate normalized feature vectors; and identifying the suspected foreign object using an image classifier, wherein the image classifier uses the normalized feature vectors as input for identifying the suspected foreign object.

Abstract: The present disclosure discloses a sample acquisition method, a target detection model generation method, a target detection method, a computing device, and a computer readable medium. The sample acquisition method includes: adding a perturbation to a pre-marked sample original box in an original image to obtain a sample selection box, wherein an image framed by the sample original box contains a target; and extracting an image framed by the sample selection box as a sample. The technical solutions of the present disclosure can effectively increase the number of the samples that can be acquired in the original image, and adding a background to the samples can effectively improve the recognition accuracy of the trained target detection model.

Abstract: The present disclosure relates to a method and an apparatus for measuring a distance using a vehicle-mounted camera, a storage medium, and an electronic device. The method includes: calibrating a camera based on camera calibration images to obtain a camera parameter; detecting parallel lane lines to obtain a vanishing point of the parallel lane lines according to the detected parallel lane lines; calculating a pitch angle of the camera according to the camera parameter and the vanishing point; determining information of an object to be detected in an image captured by the camera; and calculating a distance from the object to be detected to the camera and a size of the object to be detected according to the information of the object to be detected, the pitch angle of the camera, and the camera parameter.

Abstract: The present disclosure provides a method of determining a status of a position on a shelf, a shelf and a non-transitory computer-readable storage medium. The method includes: acquiring current detection data of the shelf in a current detection period; determining first status information of respective positions from the current detection data, in response to determining that the current detection data satisfies a preset condition; in response to the current detection data indicating that a target position whose first status information indicates the second status exists, acquiring first status information of the target position from previous detection data in a previous detection period; and determining second status information of the target position based on the first status information of the target position in the current detection data and the previous detection data respectively.

Abstract: The embodiments of the present disclosure disclose a method and apparatus for extracting an edge of an object in a depth image, a storage medium, and a computer device, to provide a solution which is simple to implement and accurate in edge extraction. The method for extracting an edge of an object in a depth image includes: calculating at least two sets of edge pixels of a first depth image using at least two edge detection algorithms; and acquiring a final set of edge pixels by combining the at least two sets of edge pixels. The solution according to the embodiments of the present disclosure is simple to implement, and may obtain a more accurate set of edge pixels, thereby obtaining an accurate pixel-level segmentation result.

Abstract: A method of encoding a watermark into a digital image is provided. The method includes partitioning an image into a plurality of blocks of a same size; accumulating the plurality of blocks of the same size into a single block image; performing a Fourier transformation on the single block image to obtain a two-dimensional Fourier spectrum defined by Fourier coefficients at different positions of a Fourier domain; inserting a watermark into a frequency domain of the two-dimensional Fourier spectrum by modifying the two-dimensional Fourier spectrum as a function of watermarking coefficients in the watermark, to obtain a modified Fourier spectrum; performing an inverse Fourier transformation on the modified Fourier spectrum to obtain a watermarked image; copying the watermarked image horizontally and vertically into a plurality of copied watermarked images; and splicing the plurality of copied watermarked images into a reconstituted watermark image.