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  • The Middle Child Problem: Revisiting Parametric Min-cut and Seeds for Object Proposals 

    Humayun, Ahmad; Li, Fuxin; Rehg, James M. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015-12)
    Object proposals have recently fueled the progress in detection performance. These proposals aim to provide category-agnostic localizations for all objects in an image. One way to generate proposals is to perform parametric ...
  • Rigid Components Identification and Rigidity Enforcement in Bearing-Only Localization using the Graph Cycle Basis 

    Tron, Roberto; Carlone, Luca; Dellaert, Frank; Daniilidis, Kostas (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015)
    Bearing-only localization can be formulated in terms of optimal graph embedding: one has to assign a 2-D or 3-D position to each node in a graph while satisfying as close as possible all the bearing-only constraints on ...
  • 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 ...
  • Lagrangian Duality in 3D SLAM: Verification Techniques and Optimal Solutions 

    Carlone, Luca; Rosen, David M.; Calafiore, Giuseppe; Leonard, John J.; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015)
    State-of-the-art techniques for simultaneous localization and mapping (SLAM) employ iterative nonlinear optimization methods to compute an estimate for robot poses. While these techniques often work well in practice, ...
  • 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 ...
  • 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 ...
  • Consistent Decentralized Graphical SLAM with Anti-Factor Down-Dating 

    Cunningham, Alexander; Indelman, Vadim; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2012-11)
    This report presents our recent and ongoing work developing a consistent decentralized data fusion approach for robust multi-robot SLAM in dangerous, unknown environments. The DDF-SAM 2.0 approach extends our previous ...
  • 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 ...
  • 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 ...
  • Predicting Daily Activities From Egocentric Images Using Deep Learning 

    Castro, Daniel; Hickson, Steven; Bettadapura, Vinay; Thomaz, Edison; Abowd, Gregory; Christensen, Henrik; Essa, Irfan (Georgia Institute of TechnologyAssociation for Computing Machinery, 2015)
    We present a method to analyze images taken from a passive egocentric wearable camera along with the contextual information, such as time and day of week, to learn and predict everyday activities of an individual. We ...
  • A Practical Approach for Recognizing Eating Moments With Wrist-Mounted Inertial Sensing 

    Thomaz, Edison; Essa, Irfan; Abowd, Gregory D. (Georgia Institute of TechnologyAssociation for Computing Machinery, 2015)
    Recognizing when eating activities take place is one of the key challenges in automated food intake monitoring. Despite progress over the years, most proposed approaches have been largely impractical for everyday usage, ...
  • 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 ...
  • Automated Assessment of Surgical Skills Using Frequency Analysis 

    Zia, Aneeq; Sharma, Yachna; Bettadapura, Vinay; Sarin, Eric L.; Clements, Mark A.; Essa, Irfan (Georgia Institute of Technology, 2015)
    We present an automated framework for visual assessment of the expertise level of surgeons using the OSATS (Objective Structured Assessment of Technical Skills) criteria. Video analysis techniques for extracting motion ...
  • 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. ...
  • 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 ...
  • Planning in the Continuous Domain: a Generalized Belief Space Approach for Autonomous Navigation in Unknown Environments 

    Indelman, Vadim; Carlone, Luca; Dellaert, Frank (Georgia Institute of Technology, 2015)
    We investigate the problem of planning under uncertainty, with application to mobile robotics. We propose a probabilistic framework in which the robot bases its decisions on the generalized belief, which is a probabilistic ...
  • 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 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, ...
  • Probabilistic Analysis of Incremental Light Bundle Adjustment 

    Indelman, Vadim; Roberts, Richard; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2013-01)
    This paper presents a probabilistic analysis of the recently introduced incremental light bundle adjustment method (iLBA) [6]. In iLBA, the observed 3D points are algebraically eliminated, resulting in a cost ...
  • Towards Planning in Generalized Belief Space 

    Indelman, Vadim; Carlone, Luca; Dellaert, Frank (Georgia Institute of Technology, 2013-12)
    We investigate the problem of planning under uncertainty, which is of interest in several robotic applications, ranging from autonomous navigation to manipulation. Recent effort from the research community has ...

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