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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

Robust Collaborative Discriminative Learning for RGB-Infrared Tracking

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Xiangyuan Lan

Hong Kong Baptist University


Mang Ye

Hong Kong Baptist University


Shengping Zhang

Harbin Institute of Technology


Pong Yuen

Hong Kong Baptist University


DOI:

10.1609/aaai.v32i1.12307


Abstract:

Tracking target of interests is an important step for motion perception in intelligent video surveillance systems. While most recently developed tracking algorithms are grounded in RGB image sequences, it should be noted that information from RGB modality is not always reliable (e.g. in a dark environment with poor lighting condition), which urges the need to integrate information from infrared modality for effective tracking because of the insensitivity to illumination condition of infrared thermal camera. However, several issues encountered during the tracking process limit the fusing performance of these heterogeneous modalities: 1) the cross-modality discrepancy of visual and motion characteristics, 2) the uncertainty of degree of reliability in different modalities, and 3) large target appearance variations and background distractions within each modality. To address these issues, this paper proposes a novel and optimal discriminative learning framework for multi-modality tracking. In particular, the proposed discriminative learning framework is able to: 1) jointly eliminate outlier samples caused by large variations and learn discriminability-consistent features from heterogeneous modalities, and 2) collaboratively perform modality reliability measurement and target-background separation. Extensive experiments on RGB-infrared image sequences demonstrate the effectiveness of the proposed method.

Topics: AAAI

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HOW TO CITE:

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen Robust Collaborative Discriminative Learning for RGB-Infrared Tracking Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen Robust Collaborative Discriminative Learning for RGB-Infrared Tracking AAAI 2018, .

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen (2018). Robust Collaborative Discriminative Learning for RGB-Infrared Tracking. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen. Robust Collaborative Discriminative Learning for RGB-Infrared Tracking. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen. 2018. Robust Collaborative Discriminative Learning for RGB-Infrared Tracking. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen. (2018) "Robust Collaborative Discriminative Learning for RGB-Infrared Tracking", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen, "Robust Collaborative Discriminative Learning for RGB-Infrared Tracking", AAAI, p., 2018.

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen. "Robust Collaborative Discriminative Learning for RGB-Infrared Tracking". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen. "Robust Collaborative Discriminative Learning for RGB-Infrared Tracking". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Xiangyuan Lan||Mang Ye||Shengping Zhang||Pong Yuen. Robust Collaborative Discriminative Learning for RGB-Infrared Tracking. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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