Three-Dimensional Feature Detection Using Optimal Steerable Filters
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A new learning strategy for object detection is presented. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform ba ...
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Typical object detection algorithms on mobile cameras suffer from the lack of a-priori knowledge on the object to be detected. The variability in the shape, pose, color distribution, and behavior affect the robustness of the detection process. In general, ...
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An algorithm for feature point tracking is proposed. The Interacting Multiple Model (IMM) filter is used to estimate the state of a feature point. The problem of data association, i.e. establishing which feature point to use in the state estimator, is solv ...
Visual attention, defined as the ability of a biological or artificial vision system to rapidly detect potentially relevant parts of a visual scene, provides a general purpose solution for low level feature detection in a vision architecture. Well consider ...
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While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. In this paper, we show that formulating the problem in ...
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