Beihang University

Xiantong Zhen

Yan Li

Xianbin Cao

Yutao Hu

Zehao Xiao

Lei Yue

Xiaolong Jiang

The present disclosure provides a dense crowd counting method and an apparatus, including: acquiring an image to be detected, where the image to be detected includes images of people; feeding the image to be detected into a convolutional neural network model to obtain a crowd density map of the image to be detected; and determining the number of the images of people in the image to be detected according to the crowd density map. Feature information of an image to be detected may be fully extracted through the above mentioned process, thereby realizing a better performance of crowd counting and density estimation, providing great convenience for subsequent security monitoring, crowd control and other applications.

Dense crowd counting method and apparatus

The present disclosure provides a target tracking method and device oriented to airborne-based monitoring scenarios. The method includes: obtaining a video to-be-tracked of the target object in real time; extracting a first frame and a second frame; trimming and capturing the first frame to derive an image for first interest region; trimming and capturing the second frame to derive an image for target template and an image for second interest region; inputting the image for target template and the image for first interest region into an appearance tracker network to derive an appearance tracking position; inputting the image for first interest region and the image for second interest region into a motion tracker network to derive a motion tracking position; and finally inputting the appearance tracking position and the motion tracking position into a deep integration network to derive a final tracking position.

Target tracking method and device oriented to airborne-based monitoring scenarios

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Beijing, China

Xiantong Zhen