3d motion classification partial image retrieval and download
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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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3d motion classification partial image retrieval and download

3D Motion ClassificationPartial Image Retrieval and Download

Multimedia Project

Multimedia and Network Lab, Department of Computer Science


Sensors and 3d motion capture system

Electrocardiogram

Sensors and 3D motion capture system

Electromyogram

Accelerometer

UTD Multimedia and Networking Lab


3d motion capture

3D Motion Capture

UTD Multimedia and Networking Lab


Integration

Integration

  • Analysis

    • Gait Analysis

  • Motion correlation and error modeling

    • Humanoid robotics

    • Game Control

    • Disease diagnostic

  • Motion Classification

    • Clustering

UTD Multimedia and Networking Lab


3d input data mocap emg

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


Input data format

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


Image data

Image data

UTD Multimedia and Networking Lab


Data analysis

Data Analysis

Data Collection

Preprocessing

Feature Extraction

Data Analysis

Geometric Trans.

Motion capture

Cross-Pair

24 Feature

Point

Gait Cycle


3d motion classification partial image retrieval and download

UTD Multimedia and Networking Lab


Project object semantics in image

+=

Project: Object Semantics in Image

  • Template-match based object semantics

  • Template-match

UTD Multimedia and Networking Lab


3d motion classification partial image retrieval and download

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


Project goal

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


Project annotated image based image and video downloader

Project: Annotated Image based Image (and Video) Downloader

  • DB- Flickr, Goolge Image…

UTD Multimedia and Networking Lab


Mit labelme project image tagging

MIT Labelme project (Image tagging)

  • http://labelme.csail.mit.edu

UTD Multimedia and Networking Lab


3d motion classification partial image retrieval and download

Query Image

Image Tagging (Annotation)

Download images

google

Flickr

Word based

image search

UTD Multimedia and Networking Lab


Project goal ii

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


Project 3d motion classification using mocap data template

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


Project goal1

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


Question

Question?

Duk-Jin Kim

[email protected]

@ECSS 4.416

Thank You !

UTD Multimedia and Networking Lab


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