earticle

논문검색

An Overview of Compressive Trackers

초록

영어

Compressive tracking is considerably popular in the visual tracking community in recent years. The very strong theoretic support from compressive sensing motivates many researchers to follow and there are a wide range of compressive trackers with attractive performances. The goal of this paper is to overview some of the most recent state-of-the-art compressive trackers in the literature. First, a variety of compressive trackers are thoroughly introduced and summarized. Second, extensive analyses from different perspectives, including random measurement matrix, compressive features, feature selection strategy and so forth, aim to provide readers a good understanding of the strengths and weaknesses of different trackers. Finally, several possible future trends for compressive trackers are outlined to hopefully bring some insights to interesting researchers.

목차

Abstract
 1. Introduction
 2. Compressive Tracking Framework
 3. Compressive Trackers
  3.1. Random Measurement Matrix and Compressive Features
  3.2. Feature Selection Strategy
  3.3. Particle Filter Framework
 4. Future Trends
 Acknowledgment
 References

저자정보

  • Zhongyi Hu Intelligent Information Systems Institute, Wenzhou University, Wenzhou 325035, Zhejiang, China
  • Lei Xiao School of Marine Science and Technology, Northwestern Polytechnic University, Xi’an 710072, Shanxi, China
  • Fei Teng School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.