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The goal of the ICASSP-2017 tutorial is to provide a concise overview of the computational aspects of human attention as applied to multimodal signal processing and multimodal (i.e., audio-visual-text) salient event detection in multimodal information streams, such as videos with audio and text.

(Part 2 of 2) While HEVC is the state-of-the-art video compression standard with profiles addressing virtually all video-related products of today, recent developments suggest significant performance improvements relative to this established technology. At the same time, the target application space evolves further towards higher picture resolution, higher dynamic range, fast motion capture, or previously unaddressed formats such as 360° video.

Recognition of visual content has been a fundamental challenge in computer vision for decades, where previous research predominantly focused on understanding visual content using a predefined yet limited vocabulary. Thanks to the recent development of deep learning techniques, researchers in both computer vision and multimedia communities are now striving to bridge vision with natural language, which can be regarded as the ultimate goal of visual understanding.

Image and video processing technologies are experiencing a rapid revolution driven by the ever-growing computational power of edge devices. Applications benefitting from this revolution include self-driving vehicles, multi-robot systems, wide-area surveillance, disaster management, and various Internet of Things applications for smart cities and smart homes. This tutorial will offer an overview of the key features and algorithms for modern multi-camera video analytics and will cover the challenges associated to their practical implementation.