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Robust Object Tracking Based on Motion Consistency.

Lijun He1, Xiaoya Qiao2, Shuai Wen3

  • 1Department of Information and Communication Engineering, School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China. jzb2016125@mail.xjtu.edu.cn.

Sensors (Basel, Switzerland)
|February 14, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a novel object tracking algorithm that improves accuracy in challenging scenarios like fast motion and occlusion. The motion consistency approach enhances target detection and appearance adaptation for reliable video analysis.

Keywords:
motion consistencyobject trackingocclusion factorposition factorstate prediction

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Area of Science:

  • Computer Vision
  • Artificial Intelligence

Background:

  • Object tracking is crucial for video surveillance and analysis.
  • Conventional algorithms struggle with fast motion and occlusions, leading to target loss.
  • Target appearance can change dynamically during tracking.

Purpose of the Study:

  • To develop an object tracking algorithm robust to fast motion and occlusion.
  • To enhance tracking accuracy by incorporating motion consistency and appearance adaptation.
  • To improve performance in challenging video surveillance scenarios.

Main Methods:

  • Proposed an object tracking algorithm based on motion consistency.
  • Utilized temporal correlation for state prediction and candidate sample generation.
  • Defined a position factor within a double Gaussian probability model for candidate sample weighting.
  • Implemented an adaptive template updating scheme for appearance changes.
  • Combined holistic and local responses with the position factor for final tracking selection.

Main Results:

  • The proposed algorithm demonstrated superior performance on a 2013 benchmark dataset.
  • Outperformed state-of-the-art algorithms in scenes with fast motion and occlusion.
  • Effectively handled target appearance variations caused by rapid movement.

Conclusions:

  • The motion consistency-based object tracking algorithm offers improved robustness.
  • The approach effectively addresses limitations of conventional trackers in dynamic environments.
  • The adaptive template updating scheme is key to handling appearance changes during tracking.