Gesture Recognition with a Focus on Important Actions by Using a Path Searching Method in Weighted Graph

12/09/2009 ∙ by Kazumoto Tanaka, et al. ∙ 0 ∙ share

This paper proposes a method of gesture recognition with a focus on important actions for distinguishing similar gestures. The method generates a partial action sequence by using optical flow images, expresses the sequence in the eigenspace, and checks the feature vector sequence by applying an optimum path-searching method of weighted graph to focus the important actions. Also presented are the results of an experiment on the recognition of similar sign language words.

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Gesture Recognition with a Focus on Important Actions by Using a Path Searching Method in Weighted Graph

Authors

Improved Optical Flow for Gesture-based Human-robot Interaction

Head Gesture Recognition using Optical Flow based Classification with Reinforcement of GMM based Background Subtraction

Two-stream Fusion Model for Dynamic Hand Gesture Recognition using 3D-CNN and 2D-CNN Optical Flow guided Motion Template

Sequence-to-Sequence Predictive Model: From Prosody To Communicative Gestures

Free-body Gesture Tracking and Augmented Reality Improvisation for Floor and Aerial Dance

Online interpretation of numeric sign language using 2-d skeletal model

Adversary Helps: Gradient-based Device-Free Domain-Independent Gesture Recognition

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