1. Motion Map: Image-based Retrieval and Segmentation of Motion Data EG SCA ’04 Speaker: Alvin Date: 11/29/2004

2. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 2 Outline  Introduction  Framework  Results  Evaluation Form  Conclusions  Future Works

3. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 3 Introduction  Provide GUI for retrieving motion data.  Using Self-organizing map. (SOM)  Only need to specify starting and ending postures.

4. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 4 SOM  A type of unsupervised learning.  Usually 1D or 2D  A mapping that preserves neighborhood relations.  All nodes in input layer are connected to all nodes in output layer.  Often used in information visualization.  Detail Detail

5. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 5 SOM Extracted from 55,114 frames of 51 data files. It took about 17 minutes on P4 2.4G for 21 * 21 nodes.

6. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 6 Clustering  Divides regions by detecting borders  The average difference against 4 neighbors  Create vertical border if  Labeling

7. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 7 Posture Icons  From the node that is nearest to the center of each clustered region.

8. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 8 Trajectory  Each motion can be represented as a trajectory.  The walking motion:

9. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 9 Virtual Node  Increase the resolution with small computation cost.  Can be preprocessed for great detail with the cost of storage.

10. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 10 Retrieval

11. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 11 Results

12. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 12 Results

13. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 13 Evaluation Form  論文簡報部份  完整性介紹 (4)  系統性介紹 (4)  表達能力 (3)  投影片製作 (3)  論文審閱部分  瞭解論文內容 (4)  結果正確性與完整性 (4)  原創性與重要性 (4)  讀後啟發與應用： The SOM can be used either for clustering or classification in my research. Besides, because the GUI is very friendly, maybe we can exploit it in our 套路 editor. Additionally, we may use the concept of LOD into the SOM.

14. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 14 Conclusions  Contributions:  Automatically  Easily Retrieve  Display motion as a trajectory  Defects:  Can’t distinguish different performers  Can’t reflect the dynamical feature

15. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 15 Future Works  Analyzing minute difference.  Zooming in the motion trajectories.  Interactive data editing.  A intuitive tool for evaluating motion graphs.  Motion blending by drawing a path.

16. Alivn/GAME Lab./CSIE/NDHUMotion Map: Image-based Retrieval and Segmentation of Motion Data 16 SOM N j denotes the total number of joints t = 0,1,2,… denotes the number of iterations.