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9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004 Stanford (California), USA. Poster Session 1. Calibration, Registration, Tracking. 9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004
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9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Poster Session 1 Calibration, Registration, Tracking
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Markerless Real-Time Target Region TrackingApplication to Frameless Stereotactic Radiosurgery T. Rohlfing1, J. Denzler2, D.B. Russakoff3, C. Gräßl4, C.R. Maurer, Jr. 5 1 Neuroscience Program, SRI International, Menlo Park, CA2 Friedrich-Schiller-Universität Jena, Jena, Germany3 Computer Science Department, Stanford University, Stanford, CA4 Universität Erlangen, Erlangen, Germany5 Department of Neurosurgery, Stanford University, Stanford, CA
Markerless Real-Time Target Region Tracking • Region tracking algorithm reliably detects 2D patient motion in X-ray projection images • Motion backprojection estimates 3D patient motion with less than 1 mm 3D target registration error • Real-time performance without implanted fiducials Motion Backprojection Reference X-ray T = 0 X-ray T = 1 Patient Motion
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Stereo and Lidar-Based Pose Estimation With Uncertainty for 3D Reconstruction Sanjit Jhala and Suresh Lodha Department of Computer Science,University of California Santa Cruz
Stereo and Lidar-Based Pose Estimation With Uncertainty for 3D Reconstruction • Presents two different approaches topose computation of mobile sensors using : lidar scan matching and stereo image matching. • Reconstruction done using real data in indoor and outdoor environments. • Pose uncertainty computation and visualization. Uncertainty for stereo- local z-axis, for lidar - local x-axis. Ideal for fusion. Stereo Based Lidar Based
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Vector Quantization Based Data Selection for Hand-Eye Calibration J. Schmidt, F. Vogt, and H. Niemann Chair for Pattern RecognitionUniversity of Erlangen-Nürnberg
Optical Tracking System Vector Quantization Based DataSelection for Hand-Eye Calibration Compute rotation R and translation t from arbitrary movements Robot Arm Errors without data selection: R≈ 0.5° - 1.0°, t ≈ 69% Errors with our approach: R ≈ 0.2° - 0.4°, t ≈ 8%
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Active Stereo for Intersection Assistance Stefan K. Gehrig, J. Klappstein, U. Franke DaimlerChrysler AG
Active Stereo for Intersection Assistance • Intersection Assistance can reduce collisions at crossings significantly • Hardware setup: Two cameras on separate Pan-Tilt-Units • Elaborate Calibration allows 3D Measurement in any direction in real-time • Cross Traffic Warning Scheme demonstrated
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Non-invasive attitude detection for full-body interaction in MEDIATE, a multisensory interactive environment for children with autism Narcís Parés, Anna Carreras, Miquel Soler Experimentation on Interactive Communication groupUniversitat Pompeu Fabra (Barcelona, Spain)
Non-invasive attitude detection for full-body interaction in MEDIATE • MEDIATE : interactive environment that generates real time stimuli (visual, aural and vibro-tactile) for children with severe autism and no verbal communication. • Goal: Children to play, explore and be creative in a predictable, controllable and safe space. • Adaptation to strong constraints set by environment and users: • wide spectrum of non-typifiable users • non invasive for full body interaction in three modalities • variable visible lighting and background • real time detection • transportability, light, safe, robust and sturdy. • SOLUTION : • 9 IR cameras + IR light illumination to obtain : • User position inside the space • User body parts and silhouette • Screens point touched by the user • CONCLUSIONS : • Well accepted by autistic children
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA A Fast Cost Relaxation Stereo Algorithm with Occlusion Detection for Mobile Robot Applications Roland Brockers, Marcus Hund, Bärbel Mertsching GET Lab, University of Paderborn, Germany
A Fast Cost Relaxation Stereo Algorithm with Occlusion Detection for Mobile Robot Applications Three step method • similarity measurement • windowed standard cross correlation • relaxation via cost function optimization • optimizing of a quadratic cost term, modeling • deviation from similarity measure • stereoscopic continuity constraint using a coupling local support area • explicit occlusion detection • using the implicit disparity probabilities • Map with the most probable displacements (white: largest displacement)
A Fast Cost Relaxation Stereo Algorithm with Occlusion Detection for Mobile Robot Applications Relaxation • optimization of a quadratic cost function leads to resolution of a linear equation system • global optimum via fast numerical algorithm Results • given for Middlebury Stereo Vision Images • 100x100 image with 20 disparity levels with 2.5 FPS
A Fast Cost Relaxation Stereo Algorithm with Occlusion Detection for Mobile Robot Applications Example original images right view groundtruth depth map left view result of similarity measurement probability for fixed displacement resulting disparity map improved result after relaxation
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA 1D camera calibration and3D reconstruction accuracy Yannick Caulier Fraunhofer Institute for Integrated Circuits IISErlangen (Germany)
3D with 1D sensors • Elaboration of a new 1D model based on 1D image construction • Design of an appropriate 3D calibration object • Determination of camera focal distance and extrinsic parameters • Calibration is validated by considering the variance of results • Reconstruction is validated with regard to the back-projection error
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Extracting Animated Meshes with Adaptive Motion Estimation Nizam Anuar and Igor Guskov University of Michigan, Ann Arborhttp://graphics.eecs.umich.edu
Shape to animated mesh • Input • Sequence of shapes • Independently meshed • Output • Animated mesh sequence • Compress, texture • Algorithm • Convert to adaptive signed distance field • Multi-Scale Optical Flow • Extract trajectories
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Automatic Generation of Shape Models Using Nonrigid Registration with a Single Segmented Template Mesh Geremy Heitz, Torsten Rohlfing, Calvin R. Maurer, Jr. Department of Electrical EngineeringStanford University
1st Mode 2nd Mode Mean Shape 3rd Mode Mean - 3SD Mean + 3SD Automatic Generation of Shape Models Using Nonrigid Registration with a Single Segmented Template Mesh • Statistical shape models provide a priori information for many image processing tasks. • Construction of a model requires segmentation of the structure of interest and the identification of correspondences in each of the training images. • We solve the segmentation and correspondence problems simultaneously, requiring only one manual segmentation in a single training set image. • To learn more, come see my poster!
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA A Probabilistic Model-Based Template Matching Approach for Robust Object Tracking in Real-Time Ch. Gräßl, T. Zinßer, and H. Nieman Chair for Pattern RecognitionUniversity of Erlangen-Nürnberg
A Probabilistic Model-Based Template Matching Approach for Robust Object Tracking in Real-Time • Combination of the hyperplane approach for template matching and the CONDENSATION algorithm for viewpoint estimation • Robust against illumination changes and cluttered background • Tolerates camera motion • Real-time capability
9th International Fall Workshop VISION, MODELING, AND VISUALIZATION 2004 November 16 - 18, 2004Stanford (California), USA Gradient-based Approach for Fine Registration of Panorama Images Hui Chen Associate professor, Shandong Univ.
Gradient-based Approach for Fine Registration of Panorama Images • We study gradient-based motion detection techniques for registration of adjacent images taken using a hand held camera for the purposes of building a panorama. • We propose a new 5-parameter model that shows better visual result and has less strict requirement on good choice of initial unknown parameters, i.e. Our 5-p model refines focal length while keeping rotational constraints, best visual result, faster than 8-p,slower than 3-p. • A quantified analysis of the relationship between the smoothing factor and the amount of disparities possible to recover: