Object recognition, i. e. classification of objects into one of several known object classes, generally is a difficult task. In this paper we address the problem of detecting an...
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter...
Traditional photometric stereo algorithms employ a Lambertian reflectance model with a varying albedo field and involve the appearance of only one object. In this paper, we gene...
Shaohua Kevin Zhou, Gaurav Aggarwal, Rama Chellapp...
We present an object recognition algorithm that uses model and image line features to locate complex objects in high clutter environments. Finding correspondences between model an...
In this paper we propose a novel method for generic object localization. The method is based on modeling the object as a graph at two levels: a local substructural representation ...