Semantic Effective Visual Codebooks by López Sastre Roberto (8 results)

Condition: New.

Condition: New. pp. 168.

Taschenbuch. Condition: Neu. Towards Semantic and Effective Visual Codebooks | Visual Vocabularies for Category-Level Object Recognition | Roberto Javier López-Sastre | Taschenbuch | 168 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846594087 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on the study of visual vocabularies for category-level object recognition. Our aim is not just to obtain more discriminative and more compact visual cod Elektronisches Buch, but to bridge the gap between visual features and semantic concepts. A novel approach for obtaining class representative visual words is presented. It is based on a maximisation procedure, i.e. the Cluster Precision Maximisation, of a novel cluster precision criterion, and on an adaptive threshold refinement scheme for agglomerative clustering algorithms based on correlation clustering techniques. A novel clustering aggregation based approach for building effective visual vocabularies is described too. It consist of a novel framework for incorporating meaningful spatial coherency among the local features into the visual codebook construction. We also propose an efficient high-dimensional data clustering algorithm, the Fast Reciprocal Nearest Neighbours. Finally, we release a new database of images called Image Collection of Annotated Real-world Objects (ICARO), which is especially designed for evaluating category-level object recognition systems. 168 pp. Englisch.

Condition: New. Print on Demand pp. 168 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 168.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book focuses on the study of visual vocabularies for category-level object recognition. Our aim is not just to obtain more discriminative and more compact visual cod Elektronisches Buch, but to bridge the gap between visual features and semantic concepts. A novel approach for obtaining class representative visual words is presented. It is based on a maximisation procedure, i.e. the Cluster Precision Maximisation, of a novel cluster precision criterion, and on an adaptive threshold refinement scheme for agglomerative clustering algorithms based on correlation clustering techniques. A novel clustering aggregation based approach for building effective visual vocabularies is described too. It consist of a novel framework for incorporating meaningful spatial coherency among the local features into the visual codebook construction. We also propose an efficient high-dimensional data clustering algorithm, the Fast Reciprocal Nearest Neighbours. Finally, we release a new database of images called Image Collection of Annotated Real-world Objects (ICARO), which is especially designed for evaluating category-level object recognition systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 168 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book focuses on the study of visual vocabularies for category-level object recognition. Our aim is not just to obtain more discriminative and more compact visual cod Elektronisches Buch, but to bridge the gap between visual features and semantic concepts. A novel approach for obtaining class representative visual words is presented. It is based on a maximisation procedure, i.e. the Cluster Precision Maximisation, of a novel cluster precision criterion, and on an adaptive threshold refinement scheme for agglomerative clustering algorithms based on correlation clustering techniques. A novel clustering aggregation based approach for building effective visual vocabularies is described too. It consist of a novel framework for incorporating meaningful spatial coherency among the local features into the visual codebook construction. We also propose an efficient high-dimensional data clustering algorithm, the Fast Reciprocal Nearest Neighbours. Finally, we release a new database of images called Image Collection of Annotated Real-world Objects (ICARO), which is especially designed for evaluating category-level object recognition systems.