2024年1月22日，Elsevier 旗下top期刊《Knowledge-Based Systems》在线发表了云南师范大学信息学院杨扬教授团队的最新研究成果《AIPT: Adaptive information perception for online multi-object tracking》。云南师范大学为第一作者兼通讯作者单位。

Abstract

Information perception is crucial in MOT tasks. Recent approaches use positional, motion, and appearance information to model object states. However, in scenes involving camera motion, tracking tasks suffer from image distortion, trajectory loss, and mismatching issues. In this paper, we propose Adaptive Information Perception for Online Multi-Object Tracking, abbreviated as AIPT. AIPT consists of an Adaptive Motion Perception Module (AMPM) and an Asymmetric Information Suppression Module (AISM). In AMPM, we design an Adaptive Image Distortion Recovery Module (AIDRM) to perceive distortions in unknown scenes, allowing the tracker to autonomously recover distorted images as the scene changes. By designing the Information-Guided Trajectory Restoration Module (IGTRM), the tracker learns object motion states from prior information and constructs accurate reconstruction information during trajectory loss. Furthermore, our AISM module utilizes masking information to suppress potential relationships between asymmetric objects, thereby enhancing the ability of tracker to handle mismatches. Both AMPM and AISM exhibit excellent scalability, seamlessly integrating with most advanced tracking methods. Ultimately, our AIPT achieves leading performance on multiple benchmark platforms, including MOT17, MOT20, and KITTI.

https://www.sciencedirect.com/science/article/abs/pii/S0950705124000042

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云南师范大学青年研究者之——杨扬

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