Baidu Online Network Technology (beijing) Co., Ltd.

Baidu Online Network Technology Co., Ltd.

Chengyue Zhang

Mingyu Chen

Yingze Bao

Le Kang

Zeyu Liu

Jian Wang

Hao Sun

Errui Ding

Shilei Wen

Xubin Li

Zhizhen Chi

Xiao Xi Liu

Hongwu Zhang

Tao Liu

Song Yang

Hongtian Yang

Jingxi Lu

Xiao Liu

The disclosure provides human-tracking methods, systems, and storage media. The method includes: acquiring a plurality of human point clouds of a current frame from a plurality of cameras; generating a total point cloud of the current frame by integrating the plurality of human point clouds of the current frame; acquiring a plurality of human point clouds of a next frame from the plurality of cameras; acquiring a total point cloud of the next frame by integrating the plurality of human point clouds of the next frame; and performing human tracking based on the total point cloud of the current frame and the total point cloud of the next frame.

Human-tracking methods, systems, and storage media

The present disclosure provides a human body recognition method and apparatus, and a storage medium, the method comprising: determining a coordinate of a target person in a three-dimensional space according to images containing the target person collected by at least two cameras; calculating back-projection errors of the target person under different cameras respectively according to the coordinate of the target person in the three-dimensional space; determining whether the cameras have a human body recognition error according to the back-projection errors of the cameras; when a camera has the human body recognition error, performing re-recognition of the target person under the camera by using person re-identification ReID, until the back-projection errors of all the cameras containing the target person are not greater than a preset threshold. The present disclosure can improve accuracy of the human body recognition result effectively.

Human body recognition method and apparatus, and storage medium

A method, apparatus, device, and storage medium for predicting the number of people of a dense crowd, including: converting a first image, in which the number of people is to be determined, into a corresponding first thermodynamic chart according to a thermodynamic chart conversion model; and determining the number of people in the first image according to the first thermodynamic chart, wherein the thermodynamic chart conversion model is obtained by training according to a pre-marked second image and a thermodynamic chart corresponding to each second image, thereby achieving prediction of the number of people of a dense crowd, improving the accuracy in predicting the number of people of the dense crowd while improving management efficiency.

Method, apparatus, device, and storage medium for predicting the number of people of dense crowd

A method, apparatus and a system for human body tracking processing, where an apparatus for video collection processing in the system has a built-in intelligent chip, and before uploading video data to a cloud server, the intelligent chip performs a pre-processing on the video data, retains a key image frame and performs a human body detection and a tracking processing on the key image frame by using human body detection tracking algorithm to acquire a first human body detection tracking result. Afterwards, the intelligent chip sends the first human body detection tracking result to the cloud server, so that the cloud server performs a human body re-identification algorithm processing and/or three-dimensional reconstruction algorithm processing on the first human body detection tracking result to acquire a second human body detection tracking result.

Method, apparatus and system for human body tracking processing

Embodiments of the present application provide an image-based position detection method, an apparatus, a device and a storage medium. Images captured at the same time by a plurality of photographing devices mounted in different orientations are acquired, where the plurality of photographing devices are synchronous in time; a two-dimensional position of a target object in each of the images is detected; and a three-dimensional position of the target object in an actual space is determined based on the two-dimensional position of the target object in each of the images and internal parameters and external parameters of the plurality of photographing devices. The embodiments of the present application implement a three-dimensional positioning solution based on a plurality of cameras, thereby improving the reliability and accuracy of object positioning.

Image-based position detection method, image based position detection apparatus, device and storage medium

A method for human motion analysis, an apparatus for human motion analysis, a device, and a storage medium. The method includes: acquiring image information captured by a number of photographing devices, where at least one of the number of photographing devices is disposed above a shelf; performing human tracking according to the image information captured by the plurality of photographing devices, and determining position information in space of at least one human body and identification information of the at least one human body; acquiring, according to the position information in space of a target human body of the at least one human body, a target image captured by the photographing device above a shelf corresponding to the position information; and recognizing an action of the target human body according to the target image and detection data of a non-visual sensor corresponding to the position information.

Method for human motion analysis, apparatus for human motion analysis, device and storage medium

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Beijing, China

Chengyue Zhang