| 基于三维模型的粒子滤波行人跟踪算法 |
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| 引用本文： | 朱梦哲,冯瑞. 基于三维模型的粒子滤波行人跟踪算法[J]. 计算机系统应用, 2016, 25(11): 112-117 |
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| 作者姓名： | 朱梦哲 冯瑞 |
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| 作者单位： | 复旦大学 计算机科学技术学院, 上海 201203;复旦大学 上海市智能信息处理重点实验室, 上海 201203;上海视频技术与系统工程研究中心, 上海 201203,复旦大学 计算机科学技术学院, 上海 201203;复旦大学 上海市智能信息处理重点实验室, 上海 201203;上海视频技术与系统工程研究中心, 上海 201203 |
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| 基金项目： | 国家科技支撑计划（2013BAH09F01）；上海市科委科技创新行动计划（14511106900） |
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| 摘 要： | 针对传统行人跟踪算法得到运动轨迹与真实轨迹差异巨大的问题，提出一种基于三维模型的粒子滤波行人跟踪算法.该方法利用摄像机标定信息和图像帧信息建立行人的三维模型，解决图像中目标尺度的变化问题，并得到目标的真实运动轨迹.同时该方法利用双指数预测模型对粒子滤波算法进行优化，以解决短时遮挡问题，同时降低运算复杂度.实验表明，基于三维模型的粒子滤波行人跟踪算法能够较准确地建立行人三维模型，对比标准粒子滤波和KPF算法，能够对行人进行有效跟踪，对短时遮挡和尺度变化有较强的鲁棒性.
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| 关 键 词： | 三维模型 粒子滤波 行人跟踪 双指数平滑 |
| 收稿时间： | 2016-02-28 |
| 修稿时间： | 2016-03-28 |
Improved Particle Filter Pedestrian Tracking Method Based on 3D Model |
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| ZHU Meng-Zhe and FENG Rui. Improved Particle Filter Pedestrian Tracking Method Based on 3D Model[J]. Computer Systems& Applications, 2016, 25(11): 112-117 |
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| Authors: | ZHU Meng-Zhe and FENG Rui |
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| Affiliation: | School of Computer Science, Fudan University, Shanghai 201203, China;Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 201203, China;Shanghai Engineering Research Center for Video Technology and System, Shanghai 201203, China and School of Computer Science, Fudan University, Shanghai 201203, China;Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 201203, China;Shanghai Engineering Research Center for Video Technology and System, Shanghai 201203, China |
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| Abstract: | To solve the problem that the trajectory based on traditional pedestrian tracking method is very different from the real trajectory, this paper proposed an improved particle filter pedestrian tracking method based on 3D model. It used camera calibration information and image sequence information to construct 3D pedestrian model, in order to deal with scale variation and extract real trajectory. And double exponential smoothing is used to improve particle filter, so it can deal with occlusion issue and reduce computation complexity. The experiment results of this paper indicates that the proposed method can cope with the situations of targets occlusion and scale variation. It has good performance in pedestrian tracking compared to standard particle filter as well as KPF. |
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| Keywords: | 3D model particle filter pedestrian tracking double exponential smoothing |
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