In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
Autonomous systems which learn and utilize a limited
visual vocabulary have wide spread applications.
Enabling such systems to segment a set of cluttered scenes
into objects is ...
Chandra Kambhamettu, Dimitris N. Metaxas, Gowri So...
This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic obj...
James M. Ferryman, Anthony D. Worrall, Stephen J. ...
Abstract. We present a method for 3D object modeling and recognition which is robust to scale and illumination changes, and to viewpoint variations. The object model is derived fro...
Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research i...
Andrea Frome, Daniel Huber, Ravi Kolluri, Thomas B...