Real-time Hand Tracking for Dynamic Gesture Recognition

Dixit, Varsha; Agrawal, Anupam

doi:10.1007/978-81-322-2220-0_12

Cited by 2 publications

(2 citation statements)

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“…Dixit and Agrawal [2] introduced real-time detection and tracking method using Adaboost algorithm based on Viola-Jones detector and Haar-like features classifier extended by Camshift algorithm and Kalman filter. Douglas Peucker method is used to extract the trajectory feature by centre position extraction.…”

Section: Related Workmentioning

confidence: 99%

“…On the other hand, dynamic hand gestures consider the static hand gestures in spatial-temporal domain since the hand region moves from one point to another point in time under different backgrounds and environmental circumstances. Dynamic hand gesture recognizes the relationship between the hand positions on successive video frames that form or draw hand trajectory [1,2,3]. In addition, a hand gesture recognition system could be used to facilitate a lot of tasks in our daily life.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hand Gesture Trajectory Estimation Using Keypoints Combination of Brisk and Minimum Eigenvalue Techniques for Human Computer Interaction Applications

Alasady¹,

Khalid²,

Sulaiman³

et al. 2017

Proceedings of the First EAI International Conference on Computer Science and Engineering

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In last years, hand gesture trajectory tracking has gained the interest a sizable body of researchers. However, in 2D vision based approaches, hand gesture trajectory estimation can be a significant challenging issue, when it comes to locate hand position in the total scene, In particular when hand practices non-linear motion, scale changes, rotation, translation and postures variation under noisy environment and different lighting conditions. In such challenges, most hand tracking techniques degrades to estimate the accurate position of hand. Hence, to increase the accuracy of moving hand position estimation, this paper proposes a method uses corner keypoints of BRISK and minimum eigenvalue techniques extracted from last segmented region of hand to create searching windows and estimate hand region position on current frame image of video sequences. The experimental outcomes revealed that the proposed algorithm can accomplish correct approximation to hand position.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%