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Space-time channel constraint correlation filtering tracking method based on suppressible abnormity

A Correlation Filtering and Channel Technology

Active Publication Date: 2021-02-05
NANJING UNIV OF POSTS & TELECOMM
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  • Abstract
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Problems solved by technology

[0007] In view of this, in order to solve the problem that the filter learning ability of the existing target tracking method is degraded when the target template is disturbed, the present invention provides a spatio-temporal channel constraint correlation filter tracking method based on suppressable abnormalities

Method used

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  • Space-time channel constraint correlation filtering tracking method based on suppressible abnormity
  • Space-time channel constraint correlation filtering tracking method based on suppressible abnormity
  • Space-time channel constraint correlation filtering tracking method based on suppressible abnormity

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Embodiment 1

[0054] see figure 1 , this embodiment provides a spatio-temporal channel constraint correlation filter tracking method based on suppressable anomalies, the method uses the lemming sequence in the target tracking benchmark data set (OTB100) as the verification set, the video size is 640*480, a total of 1336 frames , including appearance saliency changes such as illumination changes, scale scaling, occlusion, fast motion and background clutter; before using this method, that is, in the first frame, the position of the target to be tracked and the relevant filter are initialized, and then Based on the method, the target tracking of subsequent frames is completed, and the overall flow chart is as follows figure 1 As shown, the method includes the following steps:

[0055] Step S1. According to the position and scale of the target in frame t-1, obtain the area of ​​the target in frame t, take this area as the target area, and then extract the HOG feature, first depth feature and s...

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Abstract

The invention discloses a space-time channel constraint correlation filtering tracking method based on suppressible abnormity. The method comprises the steps of S1, extracting HOG features, first depth features and second depth features of a t-th frame; S2, performing fusion processing on the HOG feature, the first depth feature and the second depth feature to obtain a first fusion feature X, anddetermining the position and the scale of a target in the t-th frame of image based on the first fusion feature X and a filter; S3, according to the feature map of the t-th frame, updating the filterbased on a space-time channel constraint related filtering model capable of suppressing abnormality; and S4, repeating the step S2S4 until all frames are tracked, and finally obtaining a tracking result. According to the method, the feature representation capability of the target template is remarkably improved by combining manual features with depth features, self-adaptive channel feature selection is realized through l2, 1 norm, and the problems of boundary effect and background clutter are effectively solved.

Description

technical field [0001] The invention relates to the technical field of computer vision image processing, in particular to a method for tracking correlation filters based on suppressable anomalies. Background technique [0002] Object tracking is a very popular research topic in the field of computer vision, which has been widely used in video surveillance, unmanned driving and human-computer interaction, etc. Target tracking is to predict the position of the target in subsequent video frames given the position and scale of the target in the first frame. [0003] Trackers based on discriminative correlation filters have achieved excellent results in many public video benchmark datasets and competitions. Starting from the influential MOSSE filter, trackers based on discriminative correlation filters achieve very good performance in visual tracking. KCF uses multi-channel HOG features to build the appearance model of the target, which significantly improves the performance of...

Claims

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Application Information

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IPC IPC(8): G06T7/246G06T7/262G06K9/62
CPCG06T7/248G06T7/262G06T2207/10016G06T2207/20081G06T2207/20084G06T2207/20056G06F18/253
Inventor 范保杰王雪艳
Owner NANJING UNIV OF POSTS & TELECOMM
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