A scale self-adaptive target tracking algorithm based on kernel correlation filtering

A scale-adaptive and kernel-correlation filtering technology, applied in the field of computer vision, can solve problems such as difficult to meet the real-time requirements of the tracking system, low calculation speed, and prone to tracking drift, etc., to solve easy-to-lose targets, improve speed, and algorithm efficiency Effect

Pending Publication Date: 2019-04-26
NANJING INST OF TECH
View PDF3 Cites 35 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the above three algorithms are prone to tracking drift when the target scale changes greatly because they are mainly devoted to the improvement of target position estimation performance.
In response to this problem, Martin D et al. proposed a discriminative scale space tracking method in the articl

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
  • A scale self-adaptive target tracking algorithm based on kernel correlation filtering
  • A scale self-adaptive target tracking algorithm based on kernel correlation filtering
  • A scale self-adaptive target tracking algorithm based on kernel correlation filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] The embodiments of the present invention will be described below with reference to the accompanying drawings. The present invention can be realized through various platforms, and can also be applied in other projects. Various modifications and changes may be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention.

[0054] Please refer to figure 1 As shown, first, manually select the target rectangular area from the first frame, expand the rectangular area by 2.5 times, and determine it as a candidate area, and the scale is recorded as m×n; carry out cosine weighting on the tracking target in the rectangular frame, The 31-dimensional HOG feature map is calculated, and each dimension of the feature is input with a sample of m×n size, denoted as x 1 ,x 2 ,x 3 ,L,x 31 .

[0055] Second, construct the training sample set x of the classifier from the image block x of size m×n aro...

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 self-adaptive target tracking algorithm based on kernel correlation filtering, and belongs to the field of computer vision. The method comprises the steps of selectinga first frame of to-be-tracked target, and determining as a candidate region; Extracting gradient direction histogram (HOG) characteristics of the candidate area, and carrying out cosine weighting; Performing cyclic shift on the candidate area by using a KCF algorithm to generate a training sample, calculating a response value in a frequency domain according to a position filter obtained by sampletraining and HOG characteristics extracted by the candidate sample, and updating the target position of the current frame; Taking the target position determined by the previous frame as a center to obtain a scale filter, calculating to obtain a response value, and taking the scale corresponding to the maximum response value as the target scale of the current frame; Re-extracting the sample training filter, updating the position filter and the scale filter in a linear interpolation mode, and tracking a subsequent frame; The method can be applied to the fields of intelligent video monitoring, enterprise production automation, intelligent robots and the like.

Description

technical field [0001] The invention relates to video target tracking and belongs to the field of computer vision, in particular to a scale adaptive target tracking algorithm based on kernel correlation filtering. Background technique [0002] Object tracking is one of the important research directions in the field of computer vision, and it has a wide range of applications in public security monitoring and management, medical image analysis, behavior understanding, visual navigation, etc. At present, scholars at home and abroad are mainly concerned with the tracking robustness and accuracy improvement under the conditions of similar target interference, target scale change, blurred appearance, occlusion, and real-time performance of the target tracking system in practical applications. [0003] In recent years, target tracking algorithms based on correlation filters have begun to rise, and due to their high computational efficiency, they are gradually showing superior perfo...

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
IPC IPC(8): G06K9/42G06K9/46G06K9/62G06T7/11G06T7/168G06F17/16
CPCG06F17/16G06T7/11G06T7/168G06T2207/20056G06V10/32G06V10/462G06F18/214
Inventor 胡云层路红杨晨花湘彭俊
Owner NANJING INST OF TECH
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap