This paper presents a framework of gesture recognition and tracking using 3D camera, edge features and particle filters. A target gesture is modeled with perceptual shape features qualitatively. The perceptual model is used to guide tracking based on a particle filtering method to achieve reliable results. The system has been applied to a video game control application, Interactive Dart Game, where dart throwing gesture is modeled by learning from a training data set. The experiments are provided to demonstrate the proposed system which has a great potential for gesture analysis applications, such as sensor based video game and patient monitoring system.