@inproceedings{f6fdda3869c441c387e414bd17db8f94,
title = "Object recognition using constraints from primitive shape matching",
abstract = "In this paper, an object recognition and pose estimation approach based on constraints from primitive shape matching is presented. Additionally, an approach for primitive shape detection from point clouds using an energy minimization formulation is presented. Each primitive shape in an object adds geometric constraints on the object{\textquoteright}s pose. An algorithm is proposed to find minimal sets of primitive shapes which are sufficient to determine the complete 3D position and orientation of a rigid object. The pose is estimated using a linear least squares solver over the combination of constraints enforced by the primitive shapes. Experiments illustrating the primitive shape decomposition of object models, detection of these minimal sets, feature vector calculation for sets of shapes and object pose estimation have been presented on simulated and real data.",
author = "Nikhil Somani and Caixia Cai and Alexander Perzylo and Markus Rickert and Alois Knoll",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 10th International Symposium on Visual Computing, ISVC 2014 ; Conference date: 08-12-2014 Through 10-12-2014",
year = "2014",
doi = "10.1007/978-3-319-14249-4_75",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "783--792",
editor = "George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Drucker, {Steven M.} and Kambhamettu Chandra and Maha, {El Choubassi} and Zhigang Deng and Mark Carlson",
booktitle = "Advances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings",
}