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    Presentation en seminarioiii Presentation en seminarioiii Presentation Transcript

    • Background Problem Definition MethodologyExtraction and Tracking of a body Skeleton from Multiple views Master’s thesis proposal Alexander Pinzon Fernandez August 31, 2009 Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition MethodologyOutline 1 Background Background 2 Problem Definition Problem Objectives 3 Methodology Methodology Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Background MethodologyOutline 1 Background Background 2 Problem Definition Problem Objectives 3 Methodology Methodology Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Background MethodologyBackground The study of the human body has been of interest in several areas. For example anatomy, engineering and arts. The movement record has been used to solve different problems. Diagnosis of gait disorders. Motion capture for computer character animation [3]. Advanced ergonomics analysis and design. Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Problem Definition Objectives MethodologyOutline 1 Background Background 2 Problem Definition Problem Objectives 3 Methodology Methodology Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Problem Definition Objectives MethodologyProblem Definition Most traditional motion tracking methods are based on optical systems and present the following disadvantages: • The use of markers attached to the body ALTER the movement gesture. • The need of experts to place the markers because they must be located in specific anthropometric points. Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Problem Definition Objectives MethodologyProblem Definition The stereo systems that perform a three-dimensional reconstruction MUST handle large volumes of data of the body geometry. This process requires high-performance machines Cost between 60,000 and 130,000 dollars (Data for 2009) Qualisys AB , Sweden. 8 Oqus cameras: 100.000 USD Sports Motion, Inc . USA, California. 8 DV Cameras: 60.000 USD BTS Spa, Italy. 10 infrared cameras Smart-DDigital: 132.000 USD Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Problem Definition Objectives MethodologyDescription Project To develop a method to extract the skeleton of an articulated body, under the following conditions: • No body model. • Not having a model is an advantage because it is possible to extract and track the articulated skeleton of any body. • The extracted skeleton is a synthesized representation of the body geometry. • Once the skeleton is extracted, it is followed for each frame of the video Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Problem Definition Objectives MethodologyOutline 1 Background Background 2 Problem Definition Problem Objectives 3 Methodology Methodology Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Problem Definition Objectives MethodologyObjectives Overall Objective: To develop a method for motion tracking of the human body in 3D. Specific Objectives: 1. To implement a video-camera based system to capture a body motion, and implement the Σ − ∆ Sigma-Delta method to extract the silhouette of the body from videos. 2. To propose a method for extracting body markers which correspond to the fundamental body relations. 3. To propose a method to track the skeleton in each video-frame and validate the results. 4. To develop a system to visualize the body movement together with the estimated skeleton. Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Methodology MethodologyOutline 1 Background Background 2 Problem Definition Problem Objectives 3 Methodology Methodology Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Methodology MethodologyMethodologySkeleton Extraction and Motion Tracking • Data acquisition. • Silhouette Segmentation. • 3D Reconstruction from the data. • Skeleton extraction of the reconstructed three-dimensional object. Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Methodology MethodologyData Acquisition and SegmentationObjective: To implement a video-cameras based system to capture a body motion Video Capture system (named optical system) is divided into two problems, Camera Calibration and Synchronized Multicamera [1]. The image segmentation of this videos is realized with a set of methods for dividing an image into regions, given certain characteristics[2]. Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Methodology MethodologyThree Dimensional ReconstructionObjective: To propose a method for extracting markers of the body fundamental relationsusing the videos. 3D Reconstruction steps: Shape from silhouette Visuall Hull Find characteristic points Extract characteristic points using visual attention model Stereoscopic reconstruction Surface reconstruction with the photometric method called stereo pair, using shape and characteristic points Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Methodology MethodologySkeleton Extraction Skeleton extraction is the process of synthesizing and representing a body in a 1D structure Based on medial axis concept. Validation: • Centered skeleton is its centeredness within the object • Homotopic skeleton have the same number of connected components, tunnels, and cavities. Alexander Pinzon Fernandez Bioingenium Research Group
    • Background Problem Definition Methodology MethodologyBibliography G.K.M. Cheung, S. Baker, and T. Kanade. Visual hull alignment and refinement across time: a 3d reconstruction algorithm combining shape-from-silhouette with stereo. In Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on, volume 2, pages II–375–82 vol.2, June 2003. Ning Jin and F. Mokhtarian. Image-based shape model for view-invariant human motion recognition. In Advanced Video and Signal Based Surveillance, pages 336–341, Sept. 2007. Fabio Remondino. 3-d reconstruction of static human body shape from image sequence. Computer Vision and Image Understanding, 93:65–85, 2004. Alexander Pinzon Fernandez Bioingenium Research Group