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Pedestrian tracking method based on low-altitude aerial photographing infrared video

A pedestrian tracking and infrared technology, applied in the field of computer vision, can solve the problems of small pedestrian target and poor imaging quality, and achieve the effect of overcoming cumulative deviation, stable tracking, and good expression ability.

Active Publication Date: 2016-07-13
BEIHANG UNIV
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Problems solved by technology

[0005] In order to overcome the problems caused by poor imaging quality and small pedestrian targets of low-altitude aerial infrared video, this invention proposes a pedestrian tracking method based on low-altitude aerial infrared video, which is realized by combining Lucas-Kanade optical flow method and local area secondary detection Continuous and stable pedestrian tracking

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  • Pedestrian tracking method based on low-altitude aerial photographing infrared video

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Embodiment Construction

[0020] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0021] The present invention is based on the pedestrian tracking method of low-altitude aerial infrared video, such as figure 1 As shown, it is realized through the following steps:

[0022] Step 1: Offline training aerial infrared pedestrian support vector machine (SVM) classifier;

[0023] A. Establish a training data set for aerial infrared images of pedestrians and non-pedestrians:

[0024] Use a quadrotor UAV to carry a thermal infrared camera to collect infrared pedestrian videos at the same height (40m-60m is appropriate) in different scenes, where the camera shoots vertically downward. For an aerial infrared pedestrian video of a fixed scene, a part of the video frame image is selected, and then pedestrian and non-pedestrian training samples are manually extracted from the image. In this embodiment, a section of road aerial infrared video is select...

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Abstract

The invention discloses a pedestrian tracking method based on a low-altitude aerial photographing infrared video. Continuous and stable pedestrian tracking is realized through combination of a Lucas-Kanade optical flow method and local area secondary detection. The pedestrian tracking method comprises the steps that 1. an aerial photographing infrared pedestrian support vector machine (SVM) classifier is trained offline; 2. the initial position of a pedestrian target is determined; 3. the pedestrian target is preliminarily tracked by utilizing the LK optical flow method, and the position of the pedestrian target in the next frame is calculated; 4. a search area is set around the predicted position of the pedestrian target; and the infrared pedestrian is secondarily detected in the search area by utilizing the offline trained SVM classifier, and the position of the pedestrian target is updated; and 5. the center of the pedestrian target detected in the search area acts as input coordinates of the LK optical flow method of the next time, and the steps (3)-(5) are repeated. Continuous and stable tracking of the infrared pedestrian target can be realized by the pedestrian tracking method, and the problem of street lamp shielding can also be processed.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and relates to a pedestrian tracking method, specifically, a pedestrian tracking method based on low-altitude aerial infrared video. Background technique [0002] With the rapid development of computer vision technology, collecting pedestrian data through video has become an important research direction in the field of computer vision, and is widely used in public place monitoring, intelligent traffic monitoring system, vehicle assisted driving system development and so on. In the field of computer vision, pedestrian tracking usually refers to precisely locking the position of the same pedestrian in video or continuous frame images, which can improve the accuracy of pedestrian detection. Due to the non-rigidity of the human target, and the complex and changeable posture and appearance, the size of the far and near scales is different, coupled with the target occlusion and the randomness o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/53G06V2201/07G06F18/2411G06F18/253
Inventor 王云鹏吴新开马亚龙余贵珍王章宇
Owner BEIHANG UNIV
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