Multiscale and local search methods for real time region tracking with particle filters: local search driven by adaptive scale estimation on GPUs
Multiscale and local search methods for real time region tracking with particle filters: local search driven by adaptive scale estimation on GPUs
复制标题
DOI：
10.1007/s00138-008-0140-4
复制
发表时间：
2009-10
影响因子：
3.3
通讯作者：
R. Cabido;A. S. Montemayor;J. Pantrigo;Bryson R. Payne
中科院分区：
文献类型：
--
作者：
R. Cabido;A. S. Montemayor;J. Pantrigo;Bryson R. Payne
跟踪系统在计算机视觉中非常重要，应用于监控，人机交互等。消费者图形处理单元（GPU）在计算性能和可编程性方面都经历了非凡的发展，导致GPU更多地用于非渲染应用。在这项工作中，我们提出了一个实时目标跟踪算法，粒子滤波（PF）和多尺度局部搜索（MSLS）算法的基础上的杂交，提出了CPU和GPU架构。开发的系统在单目视频中精确跟踪单个和多个目标方面取得了成功，在GPU上以每秒70帧的速度实时运行，视频分辨率为640 × 480，比CPU版本的算法快1,100%。
Tracking systems are important in computervision, with applications in surveillance, human computer interaction, etc. Consumer graphics processing units (GPUs) have experienced an extraordinary evolution in both computing performance and programmability, leading to greater use of the GPU for non-rendering applications. In this work we propose a real-time object tracking algorithm, based on the hybridization of particle filtering (PF) and a multi-scale local search (MSLS) algorithm, presented for both CPU and GPU architectures. The developed system provides successful results in precise tracking of single and multiple targets in monocular video, operating in real-time at 70 frames per second for 640 × 480 video resolutions on the GPU, up to 1,100% faster than the CPU version of the algorithm.