Visual Object Recognition
Grauman, Kristen Lorraine, 1979-
Visual Object Recognition by Kristen Grauman, Bastian Leibe - 1st edition 2011 - 1 recurso en línea (XVII, 163 páginas) - Synthesis Lectures on Artificial Intelligence and Machine Learning 1939-4616 .
Introduction -- Overview: Recognition of Specific Objects -- Local Features: Detection and Description -- Matching Local Features -- Geometric Verification of Matched Features -- Example Systems: Specific-Object Recognition -- Overview: Recognition of Generic Object Categories -- Representations for Object Categories -- Generic Object Detection: Finding and Scoring Candidates -- Learning Generic Object Category Models -- Example Systems: Generic Object Recognition -- Other Considerations and Current Challenges -- Conclusions.
The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions.
9783031015533
10.1007/978-3-031-01553-3 doi
Visión por ordenador
Reconocimiento de formas
TA1634 / 2011 EB
Visual Object Recognition by Kristen Grauman, Bastian Leibe - 1st edition 2011 - 1 recurso en línea (XVII, 163 páginas) - Synthesis Lectures on Artificial Intelligence and Machine Learning 1939-4616 .
Introduction -- Overview: Recognition of Specific Objects -- Local Features: Detection and Description -- Matching Local Features -- Geometric Verification of Matched Features -- Example Systems: Specific-Object Recognition -- Overview: Recognition of Generic Object Categories -- Representations for Object Categories -- Generic Object Detection: Finding and Scoring Candidates -- Learning Generic Object Category Models -- Example Systems: Generic Object Recognition -- Other Considerations and Current Challenges -- Conclusions.
The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions.
9783031015533
10.1007/978-3-031-01553-3 doi
Visión por ordenador
Reconocimiento de formas
TA1634 / 2011 EB