Particle filter and perceptual hash-based video target tracking method

A perceptual hashing and particle filter technology, applied in character and pattern recognition, image analysis, image enhancement, etc., can solve the problems that the target features cannot match the template features, and cannot effectively track moving targets.

Active Publication Date: 2015-12-09
SHANDONG UNIV
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AI Technical Summary

Problems solved by technology

However, when the environment where the target is located is subject to strong illumination changes or changes in the target scale, the new tar...

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  • Particle filter and perceptual hash-based video target tracking method
  • Particle filter and perceptual hash-based video target tracking method
  • Particle filter and perceptual hash-based video target tracking method

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Embodiment Construction

[0053] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0054] The method of the present invention uses the particle filter as the framework, uses the perceptual hash value to describe the observation information of the tracking target, updates the particle weight according to the position contribution of the distance from the target and the calculated perceptual hash similarity, and finally passes the minimum variance Estimate determines the estimated location of the target. The specific process is as figure 1 shown, including the following steps:

[0055] Step 1: Select the target to be tracked in the original image as the target area, extract the perceptual hash feature of the target area as the template feature, and initialize and locate the weighted particle set;

[0056] Manually select the target to be tracked as the target area, and calculate the perceptual hash feature of the target area. The flow c...

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Abstract

The invention discloses a particle filter and perceptual hash-based video target tracking method which comprises the following steps: 1) selecting a target to be tracked from an original image as a target area, extracting a perceptual hash characteristic of the target area as a template feature, and initialization positioning a weight particle set; 2) performing a state coordinate prediction for the weight particle set and labeling the prediction area; 3) extracting the perceptual hash characteristic for each predicting particle area, and calculating a similarity degree of the predicting particle area and the target area; 4) according a position contribution of a distance from the target and a similarity degree refreshing particle weight of the perceptual hash characteristic, adopting a minimum variance to estimate and obtain a new target area; and and 5) according the size of the weight and a resample estimation value, obtaining the weight particle set of a next frame, and repeating from the step 2 to the step 4 till an end of all video sequences. The particle filter and perceptual hash-based video target tracking method disclosed by the invention is high in efficiency, and can realize fast and effective tracking on the premise of great illumination variance and change of the target scale.

Description

technical field [0001] The invention relates to a video target tracking method based on particle filtering and perceptual hashing. Background technique [0002] Video target tracking is one of the core contents in the field of computer vision. It is the process of feature detection, recognition and tracking of moving targets in the video frame sequence. After obtaining the moving features of the moving target, through further analysis and processing, to achieve The description of parameters such as the trajectory of the moving target. Moving target tracking technically involves many fields such as video processing, pattern recognition and artificial intelligence. And it has a wide range of applications in many aspects, such as public scene monitoring, intelligent transportation, medical meteorology, robot visual navigation, military visual guidance, etc. However, due to the influence of many factors such as illumination changes and real-time performance, how to achieve eff...

Claims

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Application Information

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IPC IPC(8): G06T7/20G06K9/00
CPCG06T7/20G06T2207/30232G06T2207/10016G06V20/52
Inventor 刘治曹丽君宿方琪肖晓燕张海霞袁东风
Owner SHANDONG UNIV
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