Now showing items 82-101 of 211

    • An Image Based Approach to Recovering the Gravitational Field of Asteroids 

      Melim, Andrew; Dellaert, Frank (Georgia Institute of TechnologyBritish Machine Vision Association, 2014)
      NASA’s DAWN spacecraft is on a mission to recover the gravity and structure of the asteroids Vesta and Ceres. Current approaches for developing a gravitational map of a celestial body rely upon use of the Deep ...
    • IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation 

      Forster, Christian; Carlone, Luca; Dellaert, Frank; Scaramuzza, Davide (Georgia Institute of Technology, 2015)
      Recent results in monocular visual-inertial navigation (VIN) have shown that optimization-based approaches outperform filtering methods in terms of accuracy due to their capability to relinearize past states. However, the ...
    • An In Depth View of Saliency 

      Ciptadi, Arridhana; Hermans, Tucker; Rehg, James M. (Georgia Institute of Technology, 2013-09)
      Visual saliency is a computational process that identifies important locations and structure in the visual field. Most current methods for saliency rely on cues such as color and texture while ignoring depth information, ...
    • Incremental Distributed Robust Inference from Arbitrary Robot Poses via EM and Model Selection 

      Indelman, Vadim; Michael, Nathan; Dellaert, Frank (Georgia Institute of Technology, 2014-07)
      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 data ...
    • Incremental Light Bundle Adjustment 

      Indelman, Vadim; Roberts, Richard; Beall, Chris; Dellaert, Frank (Georgia Institute of Technology, 2012-09)
      Fast and reliable bundle adjustment is essential in many applications such as mobile vision, augmented reality, and robotics. Two recent ideas to reduce the associated computational cost are structure-less SFM (structure ...
    • Incremental Light Bundle Adjustment for Robotics Navigation 

      Indelman, Vadim; Melim, Andrew; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2013-11)
      This paper presents a new computationally-efficient method for vision-aided navigation (VAN) in autonomous robotic applications. While many VAN approaches are capable of processing incoming visual observations, incorporating ...
    • Incremental Light Bundle Adjustment for Structure From Motion and Robotics 

      Indelman, Vadim; Roberts, Richard; Dellaert, Frank (Georgia Institute of TechnologyElsevier B.V., 2015)
      Bundle adjustment (BA) is essential in many robotics and structure-from-motion applications. In robotics, often a bundle adjustment solution is desired to be available incrementally as new poses and 3D points are observed. ...
    • Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping 

      Yan, Xinyan; Indelman, Vadim; Boots, Byron (Georgia Institute of Technology, 2015-09)
      Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes can represent a continuous-time trajectory, ...
    • Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping 

      Yan, Xinyan; Indelman, Vadim; Boots, Byron (Georgia Institute of Technology, 2015-07)
      Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes can represent a ...
    • Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping 

      Yan, Xinyan; Indelman, Vadim; Boots, Byron (Georgia Institute of Technology, 2014-12)
      Recent work has investigated the problem of continuous-time trajectory estimation and mapping for mobile robots by formulating the problem as sparse Gaussian process regression. Gaussian processes provide a continuous-time ...
    • Inference In The Space Of Topological Maps: An MCMC-based Approach 

      Ranganathan, Ananth; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2004-09)
      While probabilistic techniques have been considered extensively in the context of metric maps, no general purpose probabilistic methods exist for topological maps. We present the concept of Probabilistic Topological ...
    • Inferring Meal Eating Activities in Real World Settings from Ambient Sounds: A Feasibility Study 

      Thomaz, Edison; Zhang, Cheng; Essa, Irfan; Abowd, Gregory D. (Georgia Institute of TechnologyAssociation for Computing Machinery, 2015)
      Dietary self-monitoring has been shown to be an effective method for weight-loss, but it remains an onerous task despite recent advances in food journaling systems. Semi-automated food journaling can reduce the effort of ...
    • Inferring Temporal Order of Images From 3D Structure 

      Schindler, Grant; Dellaert, Frank; Kang, Sing Bing (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2007-06)
      In this paper, we describe a technique to temporally sort a collection of photos that span many years. By reasoning about persistence of visible structures, we show how this sorting task can be formulated as a constraint ...
    • Information Fusion in Navigation Systems via Factor Graph Based Incremental Smoothing 

      Indelman, Vadim; Williams, Stephen; Kaess, Michael; Dellaert, Frank (Georgia Institute of TechnologyElsevier B.V., 2013-08)
      This paper presents a new approach for high-rate information fusion in modern inertial navigation systems, that have a variety of sensors operating at different frequencies. Optimal information fusion corresponds to ...
    • Initialization Techniques for 3D SLAM: A Survey on Rotation Estimation and its Use in Pose Graph Optimization 

      Carlone, Luca; Tron, Roberto; Daniilidis, Kostas; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015-05)
      Pose graph optimization is the non-convex optimization problem underlying pose-based Simultaneous Localization and Mapping (SLAM). If robot orientations were known, pose graph optimization would be a linear least-squares ...
    • Intrinsic Localization and Mapping with 2 Applications: Diffusion Mapping and Marco Polo Localization 

      Dellaert, Frank; Alegre, Fernando; Martinson, Eric Beowulf (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2003-09)
      We investigate Intrinsic Localization and Mapping (ILM) for teams of mobile robots, a multi-robot variant of SLAM where the robots themselves are used as landmarks. We develop what is essentially a straightforward ...
    • iSAM2: Incremental Smoothing and Mapping Using the Bayes Tree 

      Kaess, Michael; Johannsson, Hordur; Roberts, Richard; Ila, Viorela; Leonard, John; Dellaert, Frank (Georgia Institute of TechnologySAGE Publications, 2012-02)
      We present a novel data structure, the Bayes tree, that provides an algorithmic foundation enabling a better understanding of existing graphical model inference algorithms and their connection to sparse matrix factorization ...
    • iSAM2: Incremental Smoothing and Mapping with Fluid Relinearization and Incremental Variable Reordering 

      Kaess, Michael; Johannsson, Hordur; Roberts, Richard; Ila, Viorela; Leonard, John; Dellaert, Frank (Georgia Institute of Technology, 2011)
      We present iSAM2, a fully incremental, graphbased version of incremental smoothing and mapping (iSAM). iSAM2 is based on a novel graphical model-based interpretation of incremental sparse matrix factorization methods, ...
    • iSAM: Fast Incremental Smoothing and Mapping with Efficient Data Association 

      Kaess, Michael; Ranganathan, Ananth; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2007-04)
      We introduce incremental smoothing and mapping (iSAM), a novel approach to the problem of simultaneous localization and mapping (SLAM) that addresses the data association problem and allows real-time application in ...
    • iSAM: Incremental Smoothing and Mapping 

      Kaess, Michael; Ranganathan, Ananth; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2008)
      We present incremental smoothing and mapping (iSAM), a novel approach to the simultaneous localization and mapping problem that is based on fast incremental matrix factorization. iSAM provides an efficient and exact ...