基于查询的对象视觉跟踪与并行序列生成
Chang Liu1, Bin Zhang1, Chunjuan Bo2
1School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
查询解码器通过并行预测目标坐标来改善对象跟踪. 这种新的方法,QPSTrack,提高了准确的对象跟踪的速度和性能.
科学领域:
- 计算机视觉 计算机视觉
- 机器学习 机器学习
- 人工智能的人工智能
背景情况:
- 查询解码器擅长对象检测,但在对象跟踪方面却很难.
- 现有的序列对序列方法将目标描述为离散的令牌.
研究的目的:
- 开发一个基于查询的平行跟踪框架,以实现高效的对象跟踪.
- 为了提高基于查询解码器的跟踪的性能和速度.
主要方法:
- 拟议的QPSTrack框架使用目标坐标序列的并行预测.
- 采用一组共同代表目标的查询,偏离一对一匹配.
- 采用了自适应解码方案,其中包括一层自适应解码器和可学习的输入.
- 用ViT-Base,ViT-Large和LeViT架构作为编码器骨干进行了实验.
主要成果:
- QPSTrack在跟踪速度和性能之间取得了良好的平衡.
- 使用ViT-Base编码器的QPSTrack-B256变种在LaSOT基准上达到69.1%的AUC.
- 通过ViT-Base编码器实现了104.8 FPS的高速.
结论:
- 用查询解码器进行并行预测对于对象跟踪是有效的.
- QPSTrack为实时对象跟踪应用提供了一个高效准确的解决方案.
- 该框架展示了与不同编码器架构的多功能性.
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