Particle filter with analytical inference for human body tracking
Particle filter with analytical inference for human body tracking
复制标题
用于人体跟踪的具有分析推理的粒子滤波器
DOI：
10.1109/motion.2002.1182229
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Soon Ki Jung
中科院分区：
文献类型：
--
作者：
M. Lee;I. Cohen;Soon Ki Jung
介绍了一种将解析推理与粒子滤波相结合的人体跟踪框架。分析推理由身体部位检测提供，并用于更新表示人体姿势的状态参数子集。这会降低随机性的程度，并减少所需的粒子数量。这一新技术是对标准粒子滤波的重大改进，具有自动初始化跟踪、从跟踪失败中恢复、减少计算量等优点。
The paper introduces a framework that integrates analytical inference into the particle filtering scheme for human body tracking. The analytical inference is provided by body parts detection, and is used to update subsets of state parameters representing the human pose. This reduces the degree of randomness and decreases the required number of particles. This new technique is a significant improvement over the standard particle filtering, with the advantages of performing automatic track initialization, recovering from tracking failures, and reducing the computational load.