Abstract
In this paper, we propose a low-cost posture recognition scheme using a single webcam for the signaling hand with nature sways and possible oc-clusions. It goes for developing the untouchable low-complexity utility based on friendly hand-posture signaling. The scheme integrates the dominant temporal-difference detection, skin color detection and morphological filtering for efficient cooperation in constructing the hand profile molds. Those molds provide representative hand profiles for more stable posture recognition than accurate hand shapes with in effect trivial details. The resultant bounding box of tracking the signaling molds can be treated as a regular-type object-matched ROI to facilitate the stable extraction of robust HOG features. With such commonly applied features on hand, the prototype SVM is adequately capable of obtaining fast and stable hand postures recognition under natural hand movement and non-hand object occlusion. Experimental results demonstrate that our scheme can achieve hand-posture recognition with enough accuracy under background clutters that the targeted hand can be allowed with medium movement and palm-grasped object. Hence, the proposed method can be easily embedded in the mobile phone as application software.
Highlights
Nowadays, the virtual reality will be expected under friendly contactless control where the recognition of hand gesture/posture is required [1] [2] for no need of wearable equipment
The resultant bounding box of tracking the signaling molds can be treated as a regular-type object-matched ROI to facilitate the stable extraction of robust histogram of oriented gradient (HOG) features
The virtual reality will be expected under friendly contactless control where the recognition of hand gesture/posture is required [1] [2] for no need of wearable equipment
Summary
The virtual reality will be expected under friendly contactless control where the recognition of hand gesture/posture is required [1] [2] for no need of wearable equipment In recent, such methods are frequently Kinect-based [1]. In this work, we develop a webcam-based hand-gesture recognition scheme to timely figure out signals of hand with national movement at very low cost. It could directly benefit the popularization of applying human computer interfaces (HCI) [9]. The novelty of best-fit bounding box purely including the bi-level hand mold is based on the efficient mutual adoption of low-level hand cues This can greatly promote the effectiveness of common features. The advantage of proposed scheme can support robust hand-posture recognition without constraints of monotonic background, occlusion-free palm, steady hand shape, fixed signaling location
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