Searching for authors named "Pierre Moreels" – sorted by Relevance.
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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. Scene images are generated by drawing a set of objects from a given database, with random clutter sprinkled on the remain
- Cited by 6 (1 self) – Add To MetaCart
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Evaluation of features detectors and descriptors based on 3d objects
- We explore the performance of a number of popular feature detectors and descriptors in matching 3D object features across viewpoints and lighting conditions. To this end we design a method, based on intersecting epipolar constraints, for providing ground truth correspondence automatically. We collec
- Cited by 8 (0 self) – Add To MetaCart
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Recognition by probabilistic hypothesis construction
- Abstract. 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 from a single training image and modeled by the visual appearance of a set of features, and their position with
- Cited by 13 (2 self) – Add To MetaCart
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- Neural network tracking and extension of positive tracking periods
- Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are loolung for the key phrases (
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