Tracking an Object over 200 FPS with the Fusion of Prior Probability and Kalman Filter-Reference-Cited by-同舟云学术

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Tracking an Object over 200 FPS with the Fusion of Prior Probability and Kalman Filter

Published:2020-02-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 12th International Conference on Machine Learning and Computing
language:
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Author:

Chen Jun¹,Zhao Jin-Hui²,Zhang Wei³,Liu Yong¹

Affiliation:

1. Cyber-Systems and Control, Zhejiang University, Hangzhou, Zhejiang, China

2. Zhejiang University of Water Resources and Electric Power, Hangzhou, Zhejiang, China

3. Fair Friend Institute of ElectroMechanics, Hangzhou Vocational & Technical College, Hangzhou, Zhejiang, China

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3383972.3384011

Reference14 articles.

1. Object tracking

2. Recent advances and trends in visual tracking: A review

3. Object Tracking for Laparoscopic Surgery Using theAdaptive Mean-Shift Kalman Algorithm

4. Annotation Supported Contour Based Object Tracking With Frame Based Error Analysis

5. Robust and Persistent Visual Tracking-by-Detection for Robotic Vision Systems

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