Now showing items 37-56 of 211

    • Data Driven MCMC for Appearance-based Topological Mapping 

      Dellaert, Frank; Ranganathan, Ananth (Georgia Institute of Technology, 2005)
      Probabilistic techniques have become the mainstay of robotic mapping, particularly for generating metric maps. In previous work, we have presented a hitherto nonexistent general purpose probabilistic framework for dealing ...
    • Data Driven MCMC for Appearance-Based Topological Mapping 

      Ranganathan, Ananth; Dellaert, Frank (Georgia Institute of TechnologyMIT Press, 2005)
      Probabilistic techniques have become the mainstay of robotic mapping, particularly for generating metric maps. In previous work, we have presented a hitherto nonexistent general purpose probabilistic framework for dealing ...
    • Data-Driven MCMC for Learning and Inference in Switching Linear Dynamic Systems 

      Oh, Sang Min; Rehg, James M.; Balch, Tucker; Dellaert, Frank (Georgia Institute of TechnologyAAAI Press, 2005-07)
      Switching Linear Dynamic System (SLDS) models are a popular technique for modeling complex nonlinear dynamic systems. An SLDS has significantly more descriptive power than an HMM, but inference in SLDS models ...
    • DDF-SAM 2.0: Consistent Distributed Smoothing and Mapping 

      Cunningham, Alexander; Indelman, Vadim; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2013-05)
      This paper presents an consistent decentralized data fusion approach for robust multi-robot SLAM in dan- gerous, unknown environments. The DDF-SAM 2.0 approach extends our previous work by combining local and neigh- borhood ...
    • DDF-SAM: Fully Distributed SLAM using Constrained Factor Graphs 

      Cunningham, Alexander; Paluri, Manohar; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2010)
      We address the problem of multi-robot distributed SLAM with an extended Smoothing and Mapping (SAM) approach to implement Decentralized Data Fusion (DDF). We present DDF-SAM, a novel method for efficiently and robustly ...
    • Decoding Children’s Social Behavior 

      Rehg, James M.; Abowd, Gregory D.; Rozga, Agata; Romero, Mario; Clements, Mark A.; Sclaroff, Stan; Essa, Irfan; Ousley, Opal Y.; Li, Yin; Kim, Chanho; Rao, Hrishikesh; Kim, Jonathan C.; Presti, Liliana Lo; Zhang, Jianming; Lantsman, Denis; Bidwell, Jonathan; Ye, Zhefan (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2013-06)
      We introduce a new problem domain for activity recognition: the analysis of children’s social and communicative behaviors based on video and audio data. We specifically target interactions between children aged 1–2 ...
    • 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 ...