Now showing items 44-63 of 215

    • Decoupling Behavior, Perception, and Control for Autonomous Learning of Affordances 

      Hermans, Tucker; Rehg, James M.; Bobick, Aaron F. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2013-05)
      A novel behavior representation is introduced that permits a robot to systematically explore the best methods by which to successfully execute an affordance-based behavior for a particular object. The approach decomposes ...
    • Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries 

      Raza, S. Hussain; Javed, Omar; Das, Aveek; Sawhney, Harpreet; Cheng, Hui; Essa, Irfan (Georgia Institute of TechnologyBritish Machine Vision Association, 2014)
      We present an algorithm to estimate depth in dynamic video scenes. We propose to learn and infer depth in videos from appearance, motion, occlusion boundaries, and geometric context of the scene. Using our method, depth ...
    • Detecting and Matching Repeated Patterns for Automatic Geo-tagging in Urban Environments 

      Schindler, Grant; Krishnamurthy, Panchapagesan; Lublinerman, Roberto; Liu, Yanxi; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2008-06)
      We present a novel method for automatically geo-tagging photographs of man-made environments via detection and matching of repeated patterns. Highly repetitive environments introduce numerous correspondence ambiguities and ...
    • Detecting Regions of Interest in Dynamic Scenes with Camera Motions 

      Kim, Kihwan; Lee, Dongryeol; Essa, Irfan (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2012-06)
      We present a method to detect the regions of interests in moving camera views of dynamic scenes with multiple moving objects. We start by extracting a global motion tendency that reflects the scene context by tracking ...
    • Differential Dynamic Programming for Optimal Estimation 

      Kobilarov, Marin; Ta, Duy-Nguyen; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015-05)
      This paper studies an optimization-based approach for solving optimal estimation and optimal control problems through a unified computational formulation. The goal is to perform trajectory estimation over extended past ...
    • Direct Superpixel Labeling for Mobile Robot Navigation Using Learned General Optical Flow Templates 

      Roberts, Richard; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2014-09)
      Towards the goal of autonomous obstacle avoidance for mobile robots, we present a method for superpixel labeling using optical flow templates. Optical flow provides a rich source of information ...
    • Dirichlet Process based Bayesian Partition Models for Robot Topological Mapping 

      Ranganathan, Ananth; Dellaert, Frank (Georgia Institute of Technology, 2004)
      Robotic mapping involves finding a solution to the correspondence problem. A general purpose solution to this problem is as yet unavailable due to the combinatorial nature of the state space. We present a framework for ...
    • Discontinuous Seam-Carving for Video Retargeting 

      Grundmann, Matthias; Kwatra, Vivek; Han, Mei; Essa, Irfan (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2010-06)
      We introduce a new algorithm for video retargeting that uses discontinuous seam-carving in both space and time for resizing videos. Our algorithm relies on a novel appearance-based temporal coherence formulation that ...
    • Distributed Navigation with Unknown Initial Poses and Data Association via Expectation Maximization 

      Indelman, Vadim; Michael, Nathan; Dellaert, Frank (Georgia Institute of Technology, 2015-02)
      We present a novel approach for multi-robot distributed and incremental inference over variables of interest, such as robot trajectories, considering the initial relative poses between the robots and multi-robot ...
    • Distributed Real-time Cooperative Localization and Mapping Using an Uncertainty-Aware Expectation Maximization Approach 

      Dong, Jing; Nelson, Erik; Indelman, Vadim; Michael, Nathan; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015-05)
      We demonstrate distributed, online, and real-time cooperative localization and mapping between multiple robots operating throughout an unknown environment sing indirect measurements. We present a novel Expectation Maximization ...
    • Duality-based Verification Techniques for 2D SLAM 

      Carlone, Luca; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015-05)
      While iterative optimization techniques for Simultaneous Localization and Mapping (SLAM) are now very efficient and widely used, none of them can guarantee global convergence to the maximum likelihood estimate. Local ...
    • Efficient and Effective Visual Codebook Generation Using Additive Kernels 

      Wu, Jianxin; Tan, Wei-Chian; Rehg, James M. (Georgia Institute of Technology, 2011-11)
      Common visual codebook generation methods used in a bag of visual words model, for example, k-means or Gaussian Mixture Model, use the Euclidean distance to cluster features into visual code words. However, most popular ...
    • Efficient Hierarchical Graph-Based Segmentation of RGBD Videos 

      Hickson, Steven; Birchfield, Stan; Essa, Irfan; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2014-06)
      We present an efficient and scalable algorithm for segmenting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based approach. Our algorithm processes a moving ...
    • Efficient Hierarchical Graph-Based Video Segmentation 

      Grundmann, Matthias; Kwatra, Vivek; Han, Mei; Essa, Irfan (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2010-06)
      We present an efficient and scalable technique for spatiotemporal segmentation of long video sequences using a hierarchical graph-based algorithm. We begin by oversegmenting a volumetric video graph into space-time ...
    • Efficient Particle Filter-Based Tracking of Multiple Interacting Targets Using an MRF-based Motion Model 

      Khan, Zia; Balch, Tucker; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2003-10)
      We describe a multiple hypothesis particle filter for tracking targets that will be influenced by the proximity and/or behavior of other targets. Our contribution is to show how a Markov random field motion prior, built ...
    • Egocentric Field-of-View Localization Using First-Person Point-of-View Devices 

      Bettadapura, Vinay; Essa, Irfan; Pantofaru, Caroline (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015-01)
      We present a technique that uses images, videos and sensor data taken from first-person point-of-view devices to perform egocentric field-of-view (FOV) localization. We define egocentric FOV localization as capturing the ...
    • Eliminating Conditionally Independent Sets in Factor Graphs: A Unifying Perspective based on Smart Factors 

      Carlone, Luca; Kira, Zsolt; Beall, Chris; Indelman, Vadim; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2014)
      Factor graphs are a general estimation framework that has been widely used in computer vision and robotics. In several classes of problems a natural partition arises among variables involved in the estimation. ...
    • EM, MCMC, and Chain Flipping for Structure from Motion with Unknown Correspondence 

      Dellaert, Frank; Seitz, Steven M.; Thorpe, Charles E.; Thrun, Sebastian (Georgia Institute of TechnologyKluwer Academic Publishers, 2003)
      Learning spatial models from sensor data raises the challenging data association problem of relating model parameters to individual measurements. This paper proposes an EM-based algorithm, which solves the model learning ...
    • The Expectation Maximization Algorithm 

      Dellaert, Frank (Georgia Institute of Technology, 2002)
      This note represents my attempt at explaining the EM algorithm. This is just a slight variation on Tom Minka's tutorial, perhaps a little easier (or perhaps not). It includes a graphical example to provide some intuition.
    • An Experimental Study of Robust Distributed Multi-Robot Data Association from Arbitrary Poses 

      Nelson, Erik; Indelman, Vadim; Michael, Nathan; Dellaert, Frank (Georgia Institute of Technology, 2014-06)
      In this work, we experimentally investigate the problem of computing the relative transformation between multiple vehicles from corresponding interrobot observations during autonomous operation in a common unknown ...