Video tracking method based on rank learning

A video tracking and ranking learning technology, applied in the field of video tracking based on ranking learning, can solve problems such as drift and lost tracked targets

Inactive Publication Date: 2014-06-25
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most detection-based video tracking algorithms can handle object changes in some real scenes, b

Method used

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  • Video tracking method based on rank learning
  • Video tracking method based on rank learning
  • Video tracking method based on rank learning

Examples

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Embodiment 1

[0114] A video tracking method based on ranking learning, comprising the following steps:

[0115] 1) Read in the initial image frame and initialize the target position parameters in is the coordinates of the upper left corner pixel of the target, w and h Indicates the width and height of the target.

[0116] 2) Extract target image block sample set and background sample set

[0117] X t 1 = { x ′ : | | l s ( x ′ ) - l s * | | ≤ α , s = 1 , t - Δt , . . . , t }

[0118] ...

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Abstract

The invention discloses a video tracking method based on rank learning. The method comprises the steps of firstly compressing multi-scale image features by using a sparse measurement matrix based on a compressed sensing theory, secondly using a Median-Flow tracking algorithm as a predictor to obtain the rough position of a target and constructing a training data set for an RV-SVM algorithm, and finally sorting training samples and taking the RV-SVM algorithm as a binary classifier to separate the target and a background to achieve the purpose of video tracking. The training process of the RV-SVM algorithm is a linear programming problem, the training time of online learning is reduced, and the efficiency of a tracking system is improved. Through the combination of multi-scale image compression feature extraction, the Median-Flow tracking algorithm and the RV-SVM algorithm, problems of target scale change, partial occlusion, 3D rotation, posture change, target fast movement and the like in a video tracking process can be effectively processed.

Description

technical field [0001] The invention belongs to the field of computer vision and pattern recognition, in particular to a video tracking method based on ranking learning. Background technique [0002] Video tracking is a key research topic in the field of computer vision, and has broad application prospects in intelligent video surveillance, augmented reality, human-computer interaction, gesture recognition, and automatic driving. In the past two decades, although researchers at home and abroad have proposed a lot of tracking algorithms, it is still a very challenging topic, because efficient video tracking algorithms need to deal with target scale changes, illumination changes, Partial occlusion, camera rotation, object deformation, etc. [0003] According to the different methods used to model the target performance, tracking algorithms can be divided into two categories: target tracking algorithms based on generative models and target tracking algorithms based on discrimi...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
Inventor 于慧敏曾雄
Owner ZHEJIANG UNIV
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