Inhaltsangabe:
THIS BOOK PRESENTS A THOROUGH OVERVIEW OF FUSION IN COMPUTER VISION, FROM AN INTERDISCIPLINARY AND MULTI-APPLICATION VIEWPOINT, DESCRIBING SUCCESSFUL APPROACHES, EVALUATED IN THE CONTEXT OF INTERNATIONAL BENCHMARKS THAT MODEL REALISTIC USE CASES. FEATURES: EXAMINES LATE FUSION APPROACHES FOR CONCEPT RECOGNITION IN IMAGES AND VIDEOS; DESCRIBES THE INTERPRETATION OF VISUAL CONTENT BY INCORPORATING MODELS OF THE HUMAN VISUAL SYSTEM WITH CONTENT UNDERSTANDING METHODS; INVESTIGATES THE FUSION OF MULTI-MODAL FEATURES OF DIFFERENT SEMANTIC LEVELS, AS WELL AS RESULTS OF SEMANTIC CONCEPT DETECTIONS, FOR EXAMPLE-BASED EVENT RECOGNITION IN VIDEO; PROPOSES ROTATION-BASED ENSEMBLE CLASSIFIERS FOR HIGH-DIMENSIONAL DATA, WHICH ENCOURAGE BOTH INDIVIDUAL ACCURACY AND DIVERSITY WITHIN THE ENSEMBLE; REVIEWS APPLICATION-FOCUSED STRATEGIES OF FUSION IN VIDEO SURVEILLANCE, BIOMEDICAL INFORMATION RETRIEVAL, AND CONTENT DETECTION IN MOVIES; DISCUSSES THE MODELING OF MECHANISMS OF HUMAN INTERPRETATION OF COMPLEX VISUAL CONTENT.
Reseña del editor:
This book presents a thorough overview of fusion in computer vision, from an interdisciplinary and multi-application viewpoint, describing successful approaches, evaluated in the context of international benchmarks that model realistic use cases. Features: examines late fusion approaches for concept recognition in images and videos; describes the interpretation of visual content by incorporating models of the human visual system with content understanding methods; investigates the fusion of multi-modal features of different semantic levels, as well as results of semantic concept detections, for example-based event recognition in video; proposes rotation-based ensemble classifiers for high-dimensional data, which encourage both individual accuracy and diversity within the ensemble; reviews application-focused strategies of fusion in video surveillance, biomedical information retrieval, and content detection in movies; discusses the modeling of mechanisms of human interpretation of complex visual content.
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