Recognizing solid objects by alignment with an image
International Journal of Computer Vision
Graphics gems IV
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Learning to Recognize and Grasp Objects
Machine Learning - Special issue on learning in autonomous robots
Probabilistic Models of Appearance for 3-D Object Recognition
International Journal of Computer Vision
Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Improved Appearance-Based 3-D Object Recognition Using Wavelets
VMV '01 Proceedings of the Vision Modeling and Visualization Conference 2001
MORAL - A Vision-Based Object Recognition System for Autonomous Mobile Systems
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
Recognition of 3D Textured Objects by Mixing View-Based and Model-Based Representations
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Autonomous Robots
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The ability to accurately localize objects in an observed scene is regarded as an important precondition for many practical applications including automatic manufacturing, quality assurance, or human-robot interaction. A popular method to recognize three-dimensional objects in two-dimensional images is to apply so-called view-based approaches. In this paper, we present an approach that uses a probabilistic view-based object recognition technique for 3D localization of rigid objects. Our system generates a set of views for each object to learn an object model which is applied to identify the 6D pose of the object in the scene. In practical experiments carried out with real image data as well as rendered images, we demonstrate that our approach is robust against changing lighting conditions and high amounts of clutter.