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Method for re-recognizing target in multi-camera monitoring network

A monitoring network, multi-camera technology, applied in character and pattern recognition, image communication, computer parts and other directions, can solve problems such as low target recognition rate

Inactive Publication Date: 2015-05-06
XIAN UNIV OF TECH
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Problems solved by technology

[0007] The purpose of the present invention is to provide a method for target re-identification in a multi-camera monitoring network, which solves the problem in the prior art that the target recognition rate is low due to the lack of full use of the correlation of each image in the image data set

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Embodiment Construction

[0090] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0091]The principle on which the present invention is based is: in actual life observation, the human eye can always accurately find the matching target in the data set, because the human eye has extracted the salience that can distinguish the target to be recognized from other targets. feature, the salient feature is highly robust to target deformation, viewing angle changes, and different lighting scenes; it can find the only optimal matching result of the target in the data set and distinguish it from other results. Intuitively, assuming that an object has certain salient regions in one camera, then when the object reappears in the field of view of other cameras, it should also have corresponding salient regions.

[0092] A method for target re-recognition in a multi-camera monitoring network of the present invention first uses visual atte...

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Abstract

The invention discloses a method for re-recognizing target in a multi-camera monitoring network. The method comprises the steps of selecting image sequences N pairs of targets between cameras i and j, and marking as a testing image sequence and a reference image sequence; solving brightness transfer functions of the cameras i and j; correcting the color of a testing image to be recognized to reach the same level as that of the reference image sequence through the brightness transfer function; respectively extracting ColorSIFI features of each image in the testing image to be recognized and the reference image sequence, and searching and matching the features; obtaining a salience image according to KNN rules; performing both-way similarity calculation according to the salience image and the ColorSIFI features; treating the reference image corresponding to the maximum similarity to be a matching target of the testing image to be recognized to recognize the target. With the adoption of the method for re-recognizing target in the multi-camera monitoring network, the problem of low target recognition rate due to incomplete utilization of incidence relation of each image in an image data set in the prior art can be solved.

Description

technical field [0001] The invention belongs to the technical field of machine vision and relates to a method for re-identifying targets in a multi-camera monitoring network. Background technique [0002] In a multi-camera monitoring and tracking network, due to too many uncertain factors of the tracked target, such as monitoring angle of view, ambient light, and target pose changes, how to re-identify the target is a difficult point. In recent years, many methods have been proposed for the problem of cross-view target tracking. During cross-view target tracking, the non-overlapping areas between cameras lead to tracking discontinuity. After the tracked target crosses the "blind zone" between cameras, the Its accurate re-identification, that is, how to build a robust appearance feature model, is a challenging problem. Extracting a robust appearance statistical feature is the core of the object re-identification problem. [0003] Therefore, someone proposes an appearance mo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00H04N7/18
CPCH04N7/181G06V20/40G06V2201/07G06F18/22
Inventor 刘龙王攀郑丽
Owner XIAN UNIV OF TECH
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