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Road pedestrian and non-motor vehicle detection method based on video analysis

A non-motor vehicle and video analysis technology, which is applied in image analysis, computer parts, image data processing, etc., can solve problems such as inability to meet real-time requirements, low detection accuracy of video images, and inability to detect pedestrians and non-motor vehicles. Achieve the effects of reducing computational complexity, improving detection efficiency and accuracy, and fast calculation speed

Active Publication Date: 2013-11-20
QINGDAO HISENSE TRANS TECH
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  • Claims
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AI Technical Summary

Problems solved by technology

[0008] In order to solve the problems of low detection accuracy of existing video images, inability to meet real-time requirements, and inability to detect pedestrians and non-motorized vehicles, the present invention provides a method for detecting road pedestrians and non-motorized vehicles based on video analysis,

Method used

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  • Road pedestrian and non-motor vehicle detection method based on video analysis
  • Road pedestrian and non-motor vehicle detection method based on video analysis

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Embodiment 1

[0065] Embodiment one, see figure 1 As shown, the present embodiment provides a method for detecting road pedestrians and non-motor vehicles based on video analysis, including:

[0066] Set the detection area step, and divide the detection area into a target entry area and a target tracking area. By setting the detection area, it is divided into a target entry area and a target tracking area. The target entry area uses a target tracking algorithm and a pattern recognition algorithm. Detect the target, and the target tracking area only uses the target tracking algorithm to detect the target. Among them, the two states of the target motion and the target are analyzed through the target tracking trajectory. The motion state is only detected in the motion area, and the static state is only detected in a smaller area. In this way, the detection range is reduced by using the moving area, and the static target tracking failure caused by only analyzing the moving area is avoided.

[...

Embodiment 2

[0076] Embodiment 2, the step of setting the detection area, the step of calibrating the scale model, and the step of detection in this embodiment are consistent with those described in Embodiment 1, and will not be repeated here. Since the tracking target may be blocked by obstacles or go out of the screen range, in order to further analyze and judge the tracking target, see figure 1 As shown, after step (3) also include:

[0077] Step (4), judge the disappearance of the tracking target. If the existing tracking target is not matched, first judge whether the disappearance condition is met according to its location. If the disappearance condition is met, perform target analysis to analyze the movement of the tracking target Trajectory and motion speed, judge and output the type of the tracking target again. When the target is about to leave the detection area, analyze the target's trajectory, speed and other characteristics, and finally determine the target attribute, that is...

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Abstract

The invention discloses a road pedestrian and non-motor vehicle detection method based on video analysis. The method comprises the steps of detection region setting and scale model calibration, including 1) performing moving region detection to a current frame image to obtain all moving regions; 2) performing target detection and tracking to the moving regions: if the moving regions are in a target entering region, firstly a tracking target matching method is adopted to perform calculation of matching the existing tracking targets with the moving regions, the moving regions which are failed to be matched are detected by adopting a mode recognition algorithm to detect moving target types and moving target position information; and if the moving regions are in a target tracking region, performing calculation of matching the existing tracking targets with the moving regions to obtain the matched positions of the tracking targets in the current frame; and 3) performing target prediction. The detection method disclosed by the invention has the advantages that the calculation complexity is effectively reduced, the calculation amount is small, the calculation speed is fast and the detection accuracy is high.

Description

technical field [0001] The invention belongs to the technical field of video analysis and processing, and in particular relates to a method for detecting road pedestrians and non-motor vehicles based on video analysis. Background technique [0002] Pedestrians and non-motor vehicles are an important part of road traffic. There have been many studies on pedestrian detection technology. Among them, the detection method using the histogram of gradient (HOG) feature combined with pattern recognition has achieved good detection results, but its The computational complexity is too high to be real-time. On this basis, other optimization methods are derived. One is to use background modeling technology or pedestrian features to obtain a preliminary positioning area and reduce the detection range. Due to the complex traffic road background and changing environment, such methods are difficult to obtain. Better detection effect. [0003] The patent application document with the publi...

Claims

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Application Information

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IPC IPC(8): G06K9/66G06T7/20
Inventor 付廷杰王彬孙婷婷王晓曼
Owner QINGDAO HISENSE TRANS TECH
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