• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.328-336
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• 2012

In this paper, we propose a robust fingertip extraction and extended Continuously Adaptive Mean Shift (CAMSHIFT) based robust hand gesture recognition for natural human-like HRI (Human-Robot Interaction). Firstly, for efficient and rapid hand detection, the hand candidate regions are segmented by the combination with robust $YC_bC_r$ skin color model and haar-like features based adaboost. Using the extracted hand candidate regions, we estimate the palm region and fingertip position from distance transformation based voting and geometrical feature of hands. From the hand orientation and palm center position, we find the optimal fingertip position and its orientation. Then using extended CAMSHIFT, we reliably track the 2D hand gesture trajectory with extracted fingertip. Finally, we applied the conditional density propagation (CONDENSATION) to recognize the pre-defined temporal motion trajectories. Experimental results show that the proposed algorithm not only rapidly extracts the hand region with accurately extracted fingertip and its angle but also robustly tracks the hand under different illumination, size and rotation conditions. Using these results, we successfully recognize the multiple hand gestures.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.316-323
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• 2010

In this paper, we propose fingertip extraction and hand motion recognition method for augmented reality applications. First, an input image is transformed into HSV color space from RGB color space. A hand area is segmented using double thresholding of H, S value, region growing, and connected component analysis. Next, the end points of the index finger and thumb are extracted using morphology operation and subtraction for a virtual keyboard and mouse interface. Finally, the angle between the end points of the index finger and thumb with respect to the center of mass point of the palm is calculated to detect the touch between the index finger and thumb for implementing the click of a mouse button. Experimental results on various input images showed that our method segments the hand, fingertips, and recognizes the movements of the hand fast and accurately. Proposed methods can be used the input interface for augmented reality applications.

• Journal of Korea Game Society
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• v.10 no.2
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• pp.49-56
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• 2010

In this paper, we propose a control method of virtual hand by the recognition of a user's hand in the virtual reality game environment. We display virtual hand on the game screen after getting the information of the user's hand movement and the direction thru input images by camera. We can utilize the movement of a user's hand as an input interface for virtual hand to select and move the object. As a hand recognition method based on the vision technology, the proposed method transforms input image from RGB color space to HSV color space, then segments the hand area using double threshold of H, S value and connected component analysis. Next, The center of gravity of the hand area can be calculated by 0 and 1 moment implementation of the segmented area. Since the center of gravity is positioned onto the center of the hand, the further apart pixels from the center of the gravity among the pixels in the segmented image can be recognized as fingertips. Finally, the axis of the hand is obtained as the vector of the center of gravity and the fingertips. In order to increase recognition stability and performance the method using a history buffer and a bounding box is also shown. The experiments on various input images show that our hand recognition method provides high level of accuracy and relatively fast stable results.