Pedestrian multi-target tracking method based on correlation clustering and space-time constraint

A correlation clustering and multi-target tracking technology, which is applied in the field of pedestrian multi-target tracking, can solve the problems of interruption of pedestrian tracking and unused space-time information of data sets, etc., and achieve the effect of improving accuracy and accurate pedestrian tracking results

Inactive Publication Date: 2020-06-30
NANJING UNIV OF SCI & TECH
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Problems solved by technology

However, cross-camera pedestrian tracking has some difficult problems in practical applications, which are mainly reflected in two aspects: on the one hand, many current tracking algorithms judge the overlap area between adjacent pedestrian detection frames by calculating Whether it belongs to the same pedestrian target, but due to the large number of objects under the surveillance video, the calculation...

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  • Pedestrian multi-target tracking method based on correlation clustering and space-time constraint
  • Pedestrian multi-target tracking method based on correlation clustering and space-time constraint
  • Pedestrian multi-target tracking method based on correlation clustering and space-time constraint

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Embodiment Construction

[0016] The present invention provides a pedestrian multi-target tracking method based on correlation clustering and time-space constraints, mainly using deep convolutional neural network to extract features, correlation clustering to complete pedestrian multi-target tracking under a single camera, and the method of time-space constraints to complete Cross-camera pedestrian multi-object tracking has three main parts. combine figure 1 , the method includes the following steps:

[0017] 1) Input the video stream to decompress the video into frames and formulate the video data set according to the selected interval;

[0018] 2) Using the video data set, use the pedestrian detection algorithm to detect each image of the video data set and obtain the detection data of pedestrians; the detection data is the minimum matrix frame information containing pedestrians;

[0019] 3) According to the matrix frame information of the pedestrian detection data, the video data set is cut to gen...

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Abstract

The invention discloses a pedestrian multi-target tracking method based on correlation clustering and space-time constraint. The method comprises the steps: pedestrian visual feature extraction, correlation clustering based on visual features, pedestrian trajectory association under a single camera, and pedestrian trajectory matching under a cross-camera condition by using a space-time constraintmethod. Aiming at the problem that pedestrian tracking under a single camera is easy to interrupt, a space-time sliding window is introduced to solve the problem; meanwhile, a space-time constraint method is introduced to associate the same pedestrian in a cross-camera scene, so pedestrian multi-target tracking in a cross-camera scene is realized; by utilizing the method provided by the invention,tracking indexes such as MOTA, MOTP and recall rate in pedestrian tracking can be consistently improved.

Description

technical field [0001] The invention relates to the fields of computer vision and pattern recognition, in particular to a pedestrian multi-target tracking method based on correlation clustering and time-space constraints. Background technique [0002] Computer Vision (Computer Vision) is a science that studies how to make machines "see". To put it further, it refers to a computer technology that uses cameras and computers instead of human eyes to identify, track and measure targets. Computer vision aims to create an artificial intelligence system that can obtain "information" from images or multidimensional data, so it has been a hot and difficult research topic in the field of computer science in recent years. [0003] As the basis of high-level vision tasks, the multi-object tracking problem has become a crucial research problem in the field of computer vision. Multiple object tracking, that is, Multiple Object Tracking (MOT). Its main task is to find an image sequence, ...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V20/42G06N3/045
Inventor 李旻先桑毅
Owner NANJING UNIV OF SCI & TECH
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