直接在压缩码流上实现超快无外观移动目标追踪
MVTrack: Ultrafast Appearance-Free Moving Object Tracking from Compressed Bitstreams
- 用运动矢量场做轻量检测，跳过像素重建
- 在VIRAT数据集上参数量少60倍，计算量少40倍
- 适合大规模监控场景的实时追踪应用
在大规模部署现代视频追踪器时，基于RGB图像的目标检测器带来巨大计算开销。为此，我们提出MVTrack，一种直接在H.264码流上运行的超快速移动物体追踪系统。MVTrack结合MVDet（轻量级运动矢量场检测器）与MVLink（极简运动关联模块）。在VIRAT数据集上，其性能优于YOLO26n，同时参数量减少60倍，浮点运算量降低40倍，CPU延迟下降8.6倍。结果表明，仅凭压缩视频数据即可实现准确且可扩展的监控追踪，无需进行像素级重建。
原文摘要 · Abstract (English)
Deploying modern video trackers at scale is bottlenecked by the computational cost of RGB-based object detectors. To this end, we present MVTrack, an ultrafast tracker for moving objects that operates directly on H.264 bitstreams. MVTrack combines MVDet, a lightweight detector for motion vector fields, with MVLink, a minimalist kinematic association module. On VIRAT, MVTrack outperforms YOLO26n while using 60$\times$ fewer parameters, requiring 40$\times$ fewer FLOPs, and reducing CPU latency by 8.6$\times$. These results demonstrate that compressed video data alone can enable accurate and scalable surveillance tracking, thereby bypassing the need for pixel reconstruction.
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