2006 · 72 citations · 3 references
ComputingComputer ScienceRobotics EngineeringComputer VisionHumanoid RoboticsMachine LearningAction RecognitionGesture AnalysisGesture RecognitionGesture-based InteractionMotion EstimationPostureEarly Action RecognitionGesture Control SystemsGesture LearningHand GesturesMotion PredictionReal-time Control AlgorithmsReal-time Control StrategiesReal-time Gesture Recognition
Early gesture recognition and motion prediction algorithms aim to provide results before gestures are completed and to forecast subsequent performer postures. The study introduces a gesture network designed to enhance the performance of early recognition and prediction algorithms. The proposed algorithm was evaluated through real‑time control experiments on a humanoid robot using gesture inputs.
This paper is concerned with an early recognition and prediction algorithm of gestures. Early recognition is the algorithm to provide recognition results before input gestures are completed. Motion prediction is the algorithm to predict the subsequent posture of the performer by using early recognition. In addition to them, this paper considers a gesture network for improving the performance of these algorithms. The performance of the proposed algorithm was evaluated by experiments of real-time control of a humanoid by gestures
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