Hand Tracking Based on Behavioral Analysis for Users

Feng, Zhiquan; Yang, Bo; Zheng, Yan-Wei; Xu, Tao; Tang, Haokui

doi:10.3724/sp.j.1001.2013.04368

Cited by 5 publications

(3 citation statements)

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“…At present, the common methods of image segmentation [13] can be divided into: Threshold segmentation method [14], edge detection method [15], region segmentation method and the method of combining the theorem of the segmentation method. Besides, Qu Jingjing [16] proposed the segmentation method of continuous frame difference and background subtraction.…”

Section: Image Segmentationmentioning

confidence: 99%

Human Computer Interaction Algorithm Based on Scene Situation Awareness

Cai¹,

Feng²,

Min³

2017

Computer Science &Amp; Information Technology (CS &Amp; IT)

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Section: Image Segmentationmentioning

confidence: 99%

Human Computer Interaction Algorithm Based on Scene Situation Awareness

Cai¹,

Feng²,

Min³

2017

Computer Science &Amp; Information Technology (CS &Amp; IT)

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“…This emphasizes the process of continuous processing in order [9]. According to Feng [10] finger motion has a certain regularity when different experimenters operate the same interaction task. In addition fingers motion has various static constraints and dynamic constraints by Thomas S. [5].…”

Section: The Definition Of Microstructurementioning

confidence: 99%

Three-Dimensional Gesture Tracking Algorithm Based on Microstructure of Hand Motion

Min¹,

Feng²

2013

2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications

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Aiming at describing human hand 3D tracking from a new perspective and reducing the time cost of hand motion tracking, a novel model-based approach to 3D hand tracking from single camera is presented. First of all this paper introduces the hand model and the virtual platform based on data glove as the basic conditions of microstructure research. Then, the basic concept of microstructure of hand motion is proposed. By applying microstructure of hand motion to exploring hand state prediction, the microstructure in the process of grasping an object is emphatically described. Finally, a human hand 3D tracking algorithm based on microstructure of hand motion is put forward. The main innovation of the algorithm is to avoid our algorithm excessively relying on the dynamic model forecast. By predicting the current state on the whole grasping process with microstructure, rather than predicting the current state on a few frames before, the proposed algorithm can sample on the most likely particles. This method avoids impossible or less likely particles as far as possible. In order to validate validity and performance of the algorithm, a great deal of experiments are completed. The results show that, compared with the particle filter (PF) gesture tracking algorithm, the proposed algorithm has low time cost.Keywords-human hand 3D tracking; particle filter; microstructure of hand motion 2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications /13 $26.00

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“…And it pointed out that the implicit humancomputer interaction technology is one of the development directions in the future. Feng Zhiquan [11] uses the context information in the gesture tracking, and has achieved a good interaction effect. Song Wei [12] uses multi-modal input and context-aware computing to combine gesture recognition into the game's scene control.…”

Section: Introductionmentioning

confidence: 99%