Add to ORKGCombining different and complementary object models promises to increase the robustness and generality of today's computer vision algorithms. This paper introduces a new method for combining different object models by determining a configuration of the models which maximizes their mutual information
International audienceIn this article, we present a general frame for a system of au tomatic modelin...
In this paper we propose an approach capable of simultaneous recognition and localization of multipl...
In many computer vision applications, objects have to be learned and recognized in images or image s...
We present a new approach to appearance-based object recognition, which captures the relationships b...
This paper proposes a reconfigurable model to recognize and detect multiclass (or multiview) objects...
In this paper a hierarchical model for pixel clustering and image segmentation is developed. In the...
Computer vision uses image processing, image understanding, and feature extraction, which is vital i...
128 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.In order to build robust comp...
Through this paper, we analyze specific branches of Artificial Intelligence (AI) technologies, such ...
[[abstract]]Surveillance of wide areas requires a system of multiple cameras to keep observing peopl...
International audienceIn this paper, we present a general frame for a system of automatic modelling ...
More often than not, visual data objects, such as images, can be described by multiplefeatures due t...
There have been many recent efforts in contentbased retrieval to perform automatic classification of...
There have been important recent advances in object recognition through the matching of invariant lo...
International audienceIn this article, we present a general frame for a system of au tomatic modelin...
International audienceIn this article, we present a general frame for a system of au tomatic modelin...
In this paper we propose an approach capable of simultaneous recognition and localization of multipl...
In many computer vision applications, objects have to be learned and recognized in images or image s...
We present a new approach to appearance-based object recognition, which captures the relationships b...
This paper proposes a reconfigurable model to recognize and detect multiclass (or multiview) objects...
In this paper a hierarchical model for pixel clustering and image segmentation is developed. In the...
Computer vision uses image processing, image understanding, and feature extraction, which is vital i...
128 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.In order to build robust comp...
Through this paper, we analyze specific branches of Artificial Intelligence (AI) technologies, such ...
[[abstract]]Surveillance of wide areas requires a system of multiple cameras to keep observing peopl...
International audienceIn this paper, we present a general frame for a system of automatic modelling ...
More often than not, visual data objects, such as images, can be described by multiplefeatures due t...
There have been many recent efforts in contentbased retrieval to perform automatic classification of...
There have been important recent advances in object recognition through the matching of invariant lo...
International audienceIn this article, we present a general frame for a system of au tomatic modelin...
International audienceIn this article, we present a general frame for a system of au tomatic modelin...
In this paper we propose an approach capable of simultaneous recognition and localization of multipl...
In many computer vision applications, objects have to be learned and recognized in images or image s...