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3D Motion Classification Partial Image Retrieval and Download

3D Motion Classification Partial Image Retrieval and Download. Multimedia Project Multimedia and Network Lab, Department of Computer Science. Electrocardiogram. Sensors and 3D motion capture system. Electromyogram. Accelerometer. 3D Motion Capture. Integration. Analysis Gait Analysis

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3D Motion Classification Partial Image Retrieval and Download

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  1. 3D Motion ClassificationPartial Image Retrieval and Download Multimedia Project Multimedia and Network Lab, Department of Computer Science

  2. Electrocardiogram Sensors and 3D motion capture system Electromyogram Accelerometer UTD Multimedia and Networking Lab

  3. 3D Motion Capture UTD Multimedia and Networking Lab

  4. Integration • Analysis • Gait Analysis • Motion correlation and error modeling • Humanoid robotics • Game Control • Disease diagnostic • Motion Classification • Clustering UTD Multimedia and Networking Lab

  5. 3D Input Data (MoCap & EMG) EMG data 3D Mocap data M x 54 Matrix ( M is the total num of Frames ) UTD Multimedia and Networking Lab

  6. Input Data Format • Each Motion is represented by set of joint vectors • Use sliding Windows for feature extractions Tibia Foot Toe Windows (Time Frame) UTD Multimedia and Networking Lab

  7. Image data UTD Multimedia and Networking Lab

  8. Data Analysis Data Collection Preprocessing Feature Extraction Data Analysis Geometric Trans. Motion capture Cross-Pair 24 Feature Point Gait Cycle

  9. UTD Multimedia and Networking Lab

  10. += Project: Object Semantics in Image • Template-match based object semantics • Template-match UTD Multimedia and Networking Lab

  11. Image template Input Image SURF(Speeded Up Robust Features) SIFT(Scale-invariant feature transfrom) HOG(Histogram of Gradients) …. Visual image semantic UTD Multimedia and Networking Lab

  12. Project Goal • Goal: Building Visual Image Semantics using template-match based approach. • Input: Image data(2D) • Training Data : Partial Image data(2D) • Output: related Spatial data(2D, Visual Image Semantics) • Requirement: • Language option: anything UTD Multimedia and Networking Lab

  13. Project: Annotated Image based Image (and Video) Downloader • DB- Flickr, Goolge Image… UTD Multimedia and Networking Lab

  14. MIT Labelme project (Image tagging) • http://labelme.csail.mit.edu UTD Multimedia and Networking Lab

  15. Query Image Image Tagging (Annotation) Download images google Flickr Word based image search UTD Multimedia and Networking Lab

  16. Project Goal (II) • Goal: Building Content based Image Downloader • Input: Image data(2D) • Training Data : Labelme Image DB • Output: collections of related Spatial data(2D) • Requirement: • Language option: anything • Lableme matlab toolbox: http://labelme.csail.mit.edu UTD Multimedia and Networking Lab

  17. Project: 3D motion classification using Mocap data template • Mocap clustering and detection Mocap based motion template Object tracking Classification 3D image (image sequence) UTD Multimedia and Networking Lab

  18. Project Goal • Goal: Cluster each motion using any machine leaning techniques to form a set of motions to decide 3D image motion set. • Window size: 360 frames with 108 frames overlapping • Input: Image Sequence data(3D) • Training Data : Mocap data (54D) • Output: Segmented image sequence data(3D) • Requirement: • Language option: anything UTD Multimedia and Networking Lab

  19. Question? Duk-Jin Kim duk-jin.kim@utdallas.edu @ECSS 4.416 Thank You ! UTD Multimedia and Networking Lab

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