Scale adaptive target tracking method based on fast compressive tracking algorithm

A scale-adaptive, compressive tracking technology, applied in the field of image processing, can solve problems such as tracking drifting targets, not well-solved, tracking drifting targets, etc., to enhance robustness, maintain real-time performance, and stabilize tracking. Effect

Active Publication Date: 2018-05-22
青岛青咨工程咨询有限公司
View PDF3 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But it mainly has two problems: First, the feature description is simple, and it is prone to tracking drift or target loss when the illumination changes or the appearance of the target changes greatly.
Second, the scale of the target window is fixed during the tracking process. When the target scale becomes larger or occluded, it is easy to cause tracking drift or target loss.
Literature [11] is the original author's improvement of the CT algorithm, but it only improves the processing speed of the algorithm, and does not solve the above problems well

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Scale adaptive target tracking method based on fast compressive tracking algorithm
  • Scale adaptive target tracking method based on fast compressive tracking algorithm
  • Scale adaptive target tracking method based on fast compressive tracking algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0075] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings and attached tables.

[0076]figure 1 It is the processing flow of the present invention. First, the input image is transformed to obtain a weighted haar-like feature image. Second, determine whether the target is blocked. When the occlusion occurs, the target is tracked in the way of block coarse search-compressed tracking and fine search. When there is no occlusion, the center of gravity coarse search-compression tracking fine search method is used to track the target. Finally, the scale of the tracking window is updated.

[0077] figure 2 is the processing flow of the compression tracking algorithm. Compressive Tracking (CT) algorithm is a popular algorithm in the binary classification method. It first uses the sparse projection matrix to reduce the dimensionality of the image features, and then uses a simple naive Bayesian classifier to reduce th...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a scale adaptive target tracking method based on a fast compressive tracking algorithm. Firstly, a context model is used to weight a quasi-Haar feature, and the robustness of the quasi-Haar feature towards illumination changes is enhanced; then, stepped tracking is adopted, the anti-blocking ability of the algorithm and the ability of the algorithm handing the target scalechanges are enhanced, and the real-time performance of the algorithm is also kept; and finally, a scale adaptive method is put forward, and stable tracking on the scale change target is realized. Goodrobustness is achieved in conditions of target scale change, target appearance change and target being blocked, the frame frequency can be ensured to be about 39 frames per second, and requirements of real-time performance are met.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to video target tracking, face recognition, online learning and scale self-adaptation, etc., in particular to a scale-adaptive target tracking method based on a fast compression tracking algorithm. Background technique [0002] Object tracking is a research hotspot in the field of computer vision, and it has a wide range of applications in motion analysis, behavior recognition, intelligent monitoring, human-computer interaction and other fields [1,2]. The difficulty of target tracking is how to deal with the changes in the appearance of the target itself and the influence of factors such as illumination, occlusion, and background changes on the target [3,4]. In recent years, the target tracking algorithm based on online learning has received extensive attention. This algorithm regards the tracking problem as a special binary classification problem. The key is to...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00
CPCG06V20/40G06F18/213G06F18/24155
Inventor 刘晴龙英冯维
Owner 青岛青咨工程咨询有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products