Now showing items 199-211 of 211

    • Understanding Egocentric Activities 

      Fathi, Alireza; Farhadi, Ali; Rehg, James M. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2011-11)
      We present a method to analyze daily activities, such as meal preparation, using video from an egocentric camera. Our method performs inference about activities, actions, hands, and objects. Daily activities are a ...
    • Using Hierarchical EM to Extract Planes from 3D Range Scans 

      Triebel, Rudolph; Burgard, Wolfram; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2005-04)
      Recently, the acquisition of three-dimensional maps has become more and more popular. This is motivated by the fact that robots act in the three-dimensional world and several tasks such as path planning or localizing ...
    • A Variational inference method for Switching Linear Dynamic Systems 

      Oh, Sang Min; Ranganathan, Ananth; Rehg, James M.; Dellaert, Frank (Georgia Institute of Technology, 2005)
      This paper aims to present a structured variational inference algorithm for switching linear dynamical systems (SLDSs) which was initially introduced by Pavlovic and Rehg. Starting with the need for the variational approach, ...
    • Video Based Assessment of OSATS Using Sequential Motion Textures 

      Sharma, Yachna; Bettadapura, Vinay; Plötz, Thomas; Hammerla, Nils; Mellor, Sebastian; McNaney, Roisin; Olivier, Patrick; Deshmukh, Sandeep; McCaskie, Andrew; Essa, Irfan (Georgia Institute of Technology, 2014)
      We present a fully automated framework for video based surgical skill assessment that incorporates the sequential and qualitative aspects of surgical motion in a data-driven manner. We replicate Objective Structured ...
    • Video Segmentation by Tracking Many Figure-Ground Segments 

      Li, Fuxin; Kim, Taeyoung; Humayun, Ahmad; Tsai, David; Rehg, James M. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2013-12)
      We propose an unsupervised video segmentation approach by simultaneously tracking multiple holistic figure-ground segments. Segment tracks are initialized from a pool of segment proposals generated from a figure-ground ...
    • Visibility Learning in Large-Scale Urban Environment 

      Alcantarilla, Pablo F.; Ni, Kai; Bergasa, Luis M.; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2011)
    • Vistas and Wall-Floor Intersection Features: Enabling Autonomous Flight in Man-made Environments 

      Ok, Kyel; Ta, Duy-Nguyen; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2012-10)
      We propose a solution toward the problem of autonomous flight and exploration in man-made indoor environments with a micro aerial vehicle (MAV), using a frontal camera, a downward-facing sonar, and an IMU. We present ...
    • Visual Odometry Priors for robust EKF-SLAM 

      Alcantarilla, Pablo F.; Bergasa, Luis Miguel; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2010)
      One of the main drawbacks of standard visual EKF-SLAM techniques is the assumption of a general camera motion model. Usually this motion model has been implemented in the literature as a constant linear and angular ...
    • Visual SLAM with a Multi-Camera Rig 

      Kaess, Michael; Dellaert, Frank (Georgia Institute of Technology, 2006)
      Camera-based simultaneous localization and mapping or visual SLAM has received much attention recently. Typically single cameras, multiple cameras in a stereo setup or omni-directional cameras are used. We propose a different ...
    • A Visualization Framework for Team Sports Captured using Multiple Static Cameras 

      Hamid, Raffay; Kumar, Ramkrishan; Hodgins, Jessica; Essa, Irfan (Georgia Institute of Technology, 2013)
      We present a novel approach for robust localization of multiple people observed using a set of static cameras. We use this location information to generate a visualization of the virtual offside line in soccer games. To ...
    • Visualizing State-Based Hypertension Progression Models 

      Gupta, Amrita; Liu, Yu-Ying; Sun, Jimeng; Rehg, James M. (Georgia Institute of Technology, 2014-11)
      We present a novel interactive visualization scheme for state-based hypertension progression modeling using hidden Markov models, applied to electronic health records of a cohort population enrolled in a hypertension ...
    • Weakly Supervised Learning of Object Segmentations from Web-Scale Video 

      Hartmann, Glenn; Grundmann, Matthias; Hoffman, Judy; Tsai, David; Kwatra, Vivek; Madani, Omid; Vijayanarasimhan, Sudheendra; Essa, Irfan A.; Rehg, James M.; Sukthankar, Rahul (Georgia Institute of TechnologySpringer-Verlag Berlin / Heidelberg, 2012-10)
      We propose to learn pixel-level segmentations of objects from weakly labeled (tagged) internet videos. Specifically, given a large collection of raw YouTube content, along with potentially noisy tags, our goal is to ...
    • What Are the Ants Doing? Vision-Based Tracking and Reconstruction of Control Programs 

      Balch, Tucker; Dellaert, Frank; Delmotte, Florent; Khan, Zia; Egerstedt, Magnus B. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2005-04)
      In this paper, we study the problem of going from a real-world, multi-agent system to the generation of control programs in an automatic fashion. In particular, a computer vision system is presented, capable of ...