1 / 23

DEVELOPMENT OF EDUCATIONAL CAMERA GAMES FOR CHILDREN

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 410073, China E-mail: xiefei2046@yahoo.com.cn. 指導教授：張元翔 中原大學 資訊工程學系 10277037 資訊碩一 劉鳳錄. 大綱.

magda
Download Presentation

DEVELOPMENT OF EDUCATIONAL CAMERA GAMES FOR CHILDREN

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 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 410073, China E-mail: xiefei2046@yahoo.com.cn 指導教授：張元翔 中原大學 資訊工程學系 10277037 資訊碩一 劉鳳錄

  2. 大綱 • 1. Abstract • 2. Introduction • 3. Developing guidelines for educational camera games • 4. Computer vision based interaction • 5. Results • 6. Summary and future work

  3. 1. ABSTRACT • The paper focuses on the computervision-based interaction style, which combines the robustnessimprovement of moving object detection by an adaptivethreshold, the moving object tracking based on modifiedcontrast context histogram feature, and finally the gesturerecognition based on the nearest neighbor.

  4. 2. INTRODUCTION • Computer games, a fast growing area of computertechnology, are extremely appealing to children andadolescents. This could easily be observed by anyone whohas connection with children and adolescents in every-daylife. In this respect, we could exploit the potential benefits ofcomputer games to make the educational process morefascinating.

  5. 3. DEVELOPING GUIDELINES FOR EDUCATIONAL CAMERA GAMES • Target group: Children of different ages • Topics: Environment protection Mathematics Topics of schooleducation • Objects: Spatial recognition, Balance control • Rules : Attractive, Intuitively • Outcomes : Drawing an animation Laudatory song • Interaction style : Vision-based games Pleasant playing experience Intuitive gestures

  6. 4. COMPUTER VISION BASED INTERACTION A. Adaptive threshold based on entropy energy B. Object tracking based on modified CCH feature-LICS C. Gesture defining and recognition

  7. ADAPTIVE THRESHOLD BASED ON ENTROPY ENERGY

  8. ADAPTIVE THRESHOLD BASED ON ENTROPY ENERGY

  9. ADAPTIVE THRESHOLD BASED ON ENTROPY ENERGY

  10. 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.

  11. OBJECT TRACKING BASED ON MODIFIED CCH FEATURE-LICS

  12. OBJECT TRACKING BASED ON MODIFIED CCH FEATURE-LICS

  13. OBJECT TRACKING BASED ON MODIFIED CCH FEATURE-LICS

  14. OBJECT TRACKING BASED ON MODIFIED CCH FEATURE-LICS

  15. GESTURE DEFINING AND RECOGNITION • The analysis of children’s 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 children’s 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.

  16. 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].

  17. 5. RESULTS

  18. 6. SUMMARY AND FUTURE WORK

  19. THANK FOR YOUR ATTENTION!!!!!肛溫蛤~ 中原大學 資訊工程學系 10277037 資訊碩一 劉鳳錄

More Related