In this work, we present an approach to jointly segment a rigid object in a 2D image and estimate its 3D pose, using the knowledge of a 3D model. We naturally couple the two proces...
Samuel Dambreville, Romeil Sandhu, Anthony J. Yezz...
Example-based methods are effective for parameter estimation problems when the underlying system is simple or the dimensionality of the input is low. For complex and high-dimensio...
Gregory Shakhnarovich, Paul A. Viola, Trevor Darre...
In this paper, we present a learning procedure called probabilistic boosting network (PBN) for joint real-time object detection and pose estimation. Grounded on the law of total p...
Jingdan Zhang, Shaohua Kevin Zhou, Leonard McMilla...
A novel method for representing 3-D objects that unifies viewer and model centered object representations is presented. A unified 3-D frequency-domain representation (called Volum...
We propose a new approach for detecting low textured
planar objects and estimating their 3D pose. Standard
matching and pose estimation techniques often depend on
texture and fe...
Stefan Holzer, Stefan Hinterstoisser, Slobodan Ili...
We present a system for fast model-based segmentation and 3D pose
estimation of specular objects using appearance based specular
features. We use observed (a) specular reflection...
This paper presents a solution to the problem of pose estimation
in the presence of heavy radial distortion and a potentially
large number of outliers. The main contribution is
...
We propose an approach to overcome the two main challenges
of 3D multiview object detection and localization:
The variation of object features due to changes in the viewpoint
an...