DEVELOPMENT OF EDUCATIONAL CAMERA GAMES FOR CHILDREN XIE Fei, CAI Shan, CHENG Ben, CHEN Chao College of Information System & Management, National University of Defense Technology, Changsha , China 1. Abstract 2. Introduction 3. Developing guidelines for educational camera games 4. Computer vision based interaction 5. Results 6. Summary and future work 1. ABSTRACT The paper focuses on the computer vision- based interaction style, which combines the robustness improvement of moving object detection by an adaptive threshold, the moving object tracking based on modified contrast context histogram feature, and finally the gesture recognition based on the nearest neighbor. 2. INTRODUCTION Computer games, a fast growing area of computer technology, are extremely appealing to children and adolescents. This could easily be observed by anyone who has connection with children and adolescents in every-day life. In this respect, we could exploit the potential benefits of computer games to make the educational process more fascinating. Target group: Children of different ages Topics: Environment protection Mathematics Topics of school education Objects: Spatial recognition, Balance control Rules : Attractive, Intuitively Outcomes : Drawing an animation Laudatory song Interaction style : Vision-based games Pleasant playing experience Intuitive gestures 3. DEVELOPING GUIDELINES FOR EDUCATIONAL CAMERA GAMES A. Adaptive threshold based on entropy energy B. Object tracking based on modified CCH feature-LICS C. Gesture defining and recognition 4. COMPUTER VISION BASED INTERACTION ADAPTIVE THRESHOLD BASED ON ENTROPY ENERGY OBJECT TRACKING BASED ON MODIFIED CCH FEATURE-LICS Chun-Rong Huang firstly presented a new invariant local descriptor, contrast context histogram (CCH), for image matching. Yu-Ting Chen, etc. bring forward a block-based background modeling method to modify CCH. LICS (Logarithm Illuminance Contrast Statistic) to improve object tracking. OBJECT TRACKING BASED ON MODIFIED CCH FEATURE-LICS GESTURE DEFINING AND RECOGNITION The analysis of childrens intuitive game- controlling gestures is twofold [19]. First, we must determine what movements children prefer in a particular game context. Second, we must study the properties and individual differences in the childrens movements in terms of components of the gesture that are repeated, range of motion, symmetry, pace, space used, and transitions from one movement to another. GESTURE DEFINING AND RECOGNITION After we have designed the interaction gestures, we firstly use our adaptive threshold based on entropy energy to separate the motion hand area form video image sequences, then track the hand based on LICS feature and Kalman filter, and then extract its trajectory eigenvector which consist of the total displacement, vertical displacement, and horizontal displacement, and finally calculate its Euclidean distance with predefined gestures. The nearest neighbor ethod is used to identify the gesture [20] [21]. 5. RESULTS 6. SUMMARY AND FUTURE WORK THANK FOR YOUR ATTENTION!!!!! ~