Fusion in Computer Vision: Understanding Complex Visual Content

Description

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.