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» Efficient Multiple Model Recognition in Cluttered 3-D Scenes
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NIPS
2004
13 years 9 months ago
Common-Frame Model for Object Recognition
A generative probabilistic model for objects in images is presented. An object consists of a constellation of features. Feature appearance and pose are modeled probabilistically. ...
Pierre Moreels, Pietro Perona
CVPR
2009
IEEE
15 years 2 months ago
From Structure-from-Motion Point Clouds to Fast Location Recognition
Efficient view registration with respect to a given 3D reconstruction has many applications like inside-out tracking in indoor and outdoor environments, and geo-locating images ...
Arnold Irschara (Graz University of Technology), C...
ECCV
2004
Springer
14 years 9 months ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona
ICCV
2009
IEEE
1136views Computer Vision» more  ICCV 2009»
15 years 19 days ago
Robust Graph-Cut Scene Segmentation and Reconstruction for Free-Viewpoint Video of Complex Dynamic Scenes
Current state-of-the-art image-based scene reconstruction techniques are capable of generating high-fidelity 3D models when used under controlled capture conditions. However, th...
Jean-Yves Guillemaut, Joe Kilner and Adrian Hilton
ICCV
2005
IEEE
14 years 1 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...