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 present disclosure relates to methods related to robot services, related systems, and readable storage media. According to some embodiments of the present disclosure, there is provided a method, including: acquiring images of an area to be served, wherein the area to be served includes serviceable grids obtained by performing equal-area grid division on the area to be served; performing pedestrian recognition on the images to acquire pedestrian heat of each serviceable grid within the preset time period; and marking a serviceable grid with the pedestrian heat exceeding a preset threshold and serviceable grids within a preset range centered on it as grids to be served, obtaining a sub-area to be served composed of the grids to be served.

Abstract: The disclosure provides an objective identification device, comprising: a classifier training circuit configured to extract objective characteristics based on training samples and perform offline training based on the objective characteristics to obtain a classifier; and a calculation circuit is configured to identify an objective in an image based on a particle swarm optimization algorithm, wherein each of particles is defined as an object having a predefined size in the image; and a fitness value of each of particles is calculated based on the classifier and the objective characteristics of the particle in the particle swarm optimization algorithm, the fitness value representing a probability that the particle belongs to the objective. The disclosure also provides an objective identification method and driving assistance device. According to the disclosure, not only the identification rate can be increased but also application scenarios having different identification rate requirements can be satisfied.

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: Provided are an image processing method, an image matching method, a device, and a storage medium. The image processing method includes: obtaining an image feature of an input image; determining a plurality of local image features of the image feature; determining a plurality of local feature vectors corresponding to the plurality of local image features respectively; determining a hash code of the input image based on the plurality of local feature vectors.

Abstract: The present disclosure relates to an image correction method and device. The method includes detecting an input image to obtain boundary straight lines. The method includes determining vertices based on the obtained boundary straight line. The method includes determining an estimated height-to-width ratio based on the obtained vertices. The method includes performing perspective transformation on the input image based on the estimated height-to-width ratio.

Abstract: An image-to-image search method includes: receiving an image to be searched and at least one category of similarity search sent by a terminal; extracting a feature code of the image by using a trained hash model that uniquely corresponds to the at least one category of similarity search according to the received image and the at least one category of similarity search; obtaining target images that are similar to the image according to the feature code of the image in a feature code library that uniquely corresponds to the at least one category of similarity search; and sending the target images to the terminal.

Abstract: A digital artwork display device, a digital artwork management method, and an electronic device are provided. The digital artwork display device includes a registration circuit, a transaction circuit, and a file decryption circuit. The registration circuit is configured to apply for a device identifier and a device public-private key pair, and the device public-private key pair includes a device public key and a device private key. The transaction circuit is configured to acquire a use license, and the use license includes the device identifier and a content key ciphertext obtained by encrypting a content key by using the device public key. The file decryption circuit is configured to decrypt the content key ciphertext in the use license by using the device private key to obtain the content key, and decrypt an encrypted file by using the content key to obtain an original file.

Abstract: An automatic object recognition method and an automatic object recognition system, a shopping device and a non-transitory computer readable storage medium are disclosed. The automatic object recognition method includes: acquiring a first image and a second image, both the first image and the second image including a same object, and the second image being a depth image; extracting a feature point of the object based on the first image; obtaining a joint feature based on the feature point from the first image and depth information of the second image; and recognizing the object based on the joint feature.

Abstract: According to the embodiments of the present disclosure, there are provided a method and device for identifying an object and a computer readable storage medium. The method includes: determining candidate categories of the object using a first neural network; and determining, in response to the candidate categories of the object having been determined, a category of the object using second neural networks respectively corresponding to the candidate categories. The device includes: a processor; a memory having stored thereon instructions which, when executed by the processor, cause the processor to: determine candidate categories of the object using a first neural network; and determine, in response to the candidate categories of the object having been determined, a category of the object using second neural networks respectively corresponding to the candidate categories.

Abstract: Embodiments of the present disclosure disclose an image detection method including: establishing a data model based on mark point information of a group of first strip-like line segments, the mark point information of each first strip-like line segment including the length, the width, the direction and the coordinate of the center point of the first strip-like line segment, establishing a priori model based on the distribution and the number of a group of second strip-like line segments which constitute a target structure, establishing a probability density function for the data model and the priori model, and performing sampling and solution optimization to obtain a globally optimal solution, and detecting the image taking the globally optimal solution as a target model. The embodiments of the present disclosure also disclose an image detection system and a non-volatile computer readable medium.

Abstract: Described herein are a method, apparatus, terminal, and system for measuring a trajectory tracking accuracy of a target. Using each method, apparatus, terminal, and system to measure the trajectory tracking accuracy of the target includes determining a location information of the actual tracking trajectory of the target; comparing the location information of the actual tracking trajectory with a location information of the target trajectory to determine a variance between the location information of the actual tracking trajectory and the location information of the target trajectory; and determining the tracking accuracy of the target based on the variance.

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 lighting device controlling circuit includes: a first switching module arranged to receive a button signal, wherein the first switching module is selectively opened or closed according to the button signal; a signal processing module coupled to the first switching module for processing the button signal to generate an adjusting signal; and a power converting module coupled to the signal processing module for changing an illuminating mode of a lighting device according to the adjusting signal.

Abstract: Aspects of the subject disclosure may include, for example, a system that provides for obtaining, by a server comprising a processor, network parameter data from an eNodeB of a wireless network. The server can determine a predicted bandwidth for a group of end user devices in a coverage area of the eNodeB according to the network parameter data. The server can receive, from an end user device of the group of end user devices, a request for the predicted bandwidth. The server can provide the predicted bandwidth to the end user device. The providing of the predicted bandwidth enables the end user device to provide a video chunk request to a content server that is based on a selected chunk delivery schedule and facilitates streaming of video content to the end user device from the content server. Other embodiments are disclosed.

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: 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: 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: 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 an image correction method and device. The method includes: correcting a target face image; obtaining first eye position information and second eye position information through calculation according to the face image; obtaining a first image correction parameter and a second image correction parameter via calculation based on the first eye position information and the second eye position information; and correcting a first image according to the first image correction parameter and correcting a second image according to the second image correction parameter.