Freehand Tracking Based on Behavioral Model Analysis

Zhiquan Feng, Yanwei Zheng, Bo Yang, Wei Gai, Yi Li, Yan Lin, Haokui Tang, XianHui Song
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Abstract

A novel framework for 3D freehand tracking is put forward in this paper. Firstly, we model and investigate this problem under our virtual assembly system (VAS), so as to decrease the arbitrariness and complexity of this issue. Secondly, we put emphasis on building cognitive and behavioral model (BM) for users in VAS. Thirdly, we research on the way to track 3D freehand based on BM. Our experimental results show that the proposed approach raises the quality of each sampled particle or avoid sampling "poor" particles which appear with low probability in each frame, and it tracks 3D freehand in real-time with high accuracy. The number of the drawn particles is reduced up to 5 and the tracking speed increase up to 81 ms per frame.
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基于行为模型分析的徒手跟踪
提出了一种新的三维徒手跟踪框架。首先,在虚拟装配系统(VAS)下对该问题进行建模和研究,降低了该问题的随意性和复杂性。其次,重点构建VAS用户认知与行为模型(BM)。第三,研究了基于BM的三维徒手跟踪方法。实验结果表明,该方法提高了每个采样粒子的质量或避免了每帧中出现概率较低的“差”粒子的采样,能够以较高的精度实时跟踪三维徒手。绘制的粒子数量减少到5个,跟踪速度增加到每帧81毫秒。
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