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

Zepp Labs, Inc.

Baidu Online Network Technology Co., Ltd.

Zeyu Liu

Mingyu Chen

Yingze Bao

Le Kang

Jian Wang

Hao Sun

Errui Ding

Shilei Wen

Xubin Li

Chengyue Zhang

Xiao Xi Liu

Zhizhen Chi

Hongwu Zhang

Tao Liu

Song Yang

Zhigang Wang

Zheng Han

Xiaowei Dai

Jiangyu Liu

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 human body tracking method, apparatus, and device, and a storage medium. The method includes: obtaining a current frame image captured by a target photographing device at a current moment; detecting each human body in the current frame image to obtain first position information of the each human body in the current frame image; calculating second position information of a first human body in the current frame image; determining target position information of the each human body in the current frame image according to the second position information of the first human body in the current frame image, the first position information of the each human body in the current frame image, and pedestrian features of all tracked pedestrians stored in a preset list.

Human body tracing method, apparatus and device, 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

A system is provided for real-time single-view action recognition for sports videos based on key pose analysis of the sports videos. A training module of the system trains feature models for a sports action distinctively associated with each sports type using a large corpus of training videos. The trained feature models include a player detector for detecting locations of a player in video frames of a training video, a set of key pose identifiers for identifying distinctive poses of a sports action associated with a type of sports, and a meta classifier for determining a likelihood that the sports action has happened in a sports video based on the key poses analysis. Responsive to an input sports video being received for real-time action recognition, a set of trained feature models associated with the sports type of the input video are selected and applied to the input video.

Real-time single-view action recognition based on key pose analysis for sports videos

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Beijing, China

Zeyu Liu