A Robust Method for Hand Gesture Segmentation and Recognition Using Forward Spotting Scheme in Conditional Random Fields

This paper proposes a forward spotting method that handles hand gesture segmentation and recognition simultaneously without time delay. To spot meaningful gestures of numbers (0-9) accurately, a stochastic method for designing a non-gesture model using Conditional Random Fields (CRFs) is proposed without training data. The non-gesture model provides a confidence measures that are used as an adaptive threshold to find the start and the end point of meaningful gestures. Experimental results show that the proposed method can successfully recognize isolated gestures with 96.51% and meaningful gestures with 90.49% reliability.