• 3D Pose Estimation of Daily Objects Using an RGB-D Camera 

      Choi, Changhyun; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2012-10)
      In this paper, we present an object pose estimation algorithm exploiting both depth and color information. While many approaches assume that a target region is cleanly segmented from background, our approach does not rely ...
    • 3D Textureless Object Detection and Tracking: An Edge-based Approach 

      Choi, Changhyun; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2012-10)
      This paper presents an approach to textureless object detection and tracking of the 3D pose. Our detection and tracking schemes are coherently integrated in a particle filtering framework on the special Euclidean group, ...
    • Cognitive vision for efficient scene processign and object categorization in highly cluttered environments 

      Choi, Changhyun; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2009-10)
      One of the key competencies required in modern robots is finding objects in complex environments. For the last decade, significant progress in computer vision and machine learning literatures has increased the recognition ...
    • Real-time 3d model-based tracking using edge and keypoint features for robotic manipulation 

      Choi, Changhyun; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2010-05)
      We propose a combined approach for 3D real-time object recognition and tracking, which is directly applicable to robotic manipulation. We use keypoints features for the initial pose estimation. This pose estimate serves ...
    • Robust 3D visual tracking using particle filtering on the SE(3) group 

      Choi, Changhyun; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2011-05)
      In this paper, we present a 3D model-based object tracking approach using edge and keypoint features in a particle filtering framework. Edge points provide 1D information for pose estimation and it is natural to consider ...
    • Robust 3D Visual Tracking Using Particle Filtering on the Special Euclidean Group: A Combined Approach of Keypoint and Edge Features 

      Choi, Changhyun; Christensen, Henrik I. (Georgia Institute of TechnologySAGE Publications, 2012-03-07)
      We present a 3D model-based visual tracking approach using edge and keypoint features in a particle filtering framework. Recently, particle filtering based approaches have been proposed to integrate multiple pose hypotheses ...