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» A New Bayesian Framework for Object Recognition
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CVPR
2005
IEEE
14 years 9 months ago
Bayesian Object Detection in Dynamic Scenes
Detecting moving objects using stationary cameras is an important precursor to many activity recognition, object recognition and tracking algorithms. In this paper, three innovati...
Yaser Sheikh, Mubarak Shah
IJCV
2000
164views more  IJCV 2000»
13 years 6 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann
ICCV
2001
IEEE
14 years 9 months ago
Recognizing Large 3-D Objects through Next View Planning using an Uncalibrated Camera
We present a new on-line scheme for the recognition and pose estimation of a large isolated 3-D object, which may not entirely fit in a camera's field of view. We do not assu...
Sumantra Dutta Roy, Santanu Chaudhury, Subhashis B...
ICPR
2000
IEEE
14 years 8 months ago
Invariant Image Object Recognition Using Mixture Densities
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
Daniel Keysers, Hermann Ney, Jörg Dahmen, Mar...
ICVGIP
2004
13 years 8 months ago
Active 3-D Object Recognition Using Appearance-Based Aspect Graphs
We present a new active active recognition scheme (using an uncalibrated camera) based on a new idea, appearancebased aspect graphs. The scheme is robust to background clutter, an...
Sumantra Dutta Roy, Nirupama Kulkarni