Visual Event Computing by WeiQi Yan, Jonathan Weir & Ventus Publishing ApS

visual-event-computingIn this book, the focus is on visual event computing. The events come from video and images. An introduction is presented on what and event is, then an introduction is presented on detecting event from videos and images. Furthermore, event search, retrieval, mining, and reasoning is examined and discussed. As an example, how to use visual event computing in surveillance environment is proposed. The related software system is also presented. An event in the general sense is defined as something that happens at a given place and time. The basic characteristics of an event to be considered in the sense of human centric computing systems are it ID, time, location and description, Events that take place at different times or positions are considered to be different events. People experience events associated with media either as a combination, e.g. video and audio or individually. With the advent of new types of media, and the increasing diversity of media for capturing events, event-computing has emerged as new research area. Previously, most work focused on event detection; however, recent work has started to address other functionalities such as storage, reasoning, interaction and exploration. Consequently, new disciplines, such as data mining, have had to be embraced. The definition of an event in terms of visual computing is something that still had to embrace. The definition of an event in terms of visual computing is something that still has to be formally defined, throughout this book, a discussion is presented on the definition of an event in the hope of giving the reader a clear sense of what an event is seen as, even though this concept is still under discussion within visual computing.


In this book the readers will read Introduction to Visual Event Computing, Events, Towards events, Event types, Event aspects, Event relationships, Defining events, Experimental data, Create a web, Explicit referential links, Spatio-Temporal links, IE: EventoScope, Causality, Causal chains, A Scenario – Conferences, Crowd sourcing, Participatory Urban sensing, Visual event computing, Content of event computing, Event operations, Event storage, Modeling techniques to facilitate event presentation, Event mining and reasoning, Applied techniques in event computing, Visual event capturing, Live data, Photo event detection, Video event detection, Event detection from sports video, Event detection from surveillance video, Meeting event detection from indoors scenes, Multi-modal event computing, Multi-modal event capturing in a sentient environment, Document web and event web, SEraja Structure, Event-based analysis of multi-modal data, Approaches, Capture events using requirement-specific sensors, Store all events from a specific environment in an event server using E, Develop aggregation ; crawling approach to create a situation model for the environment, Develop event interaction environment, Event detection systems, Event environments, Types of events to be detection, Sensors are sources of event information, Environment model, Detecting events, Detecting methods, Automatic or semi-automatic, Reports, Videos, Audio, and sensory data, Privacy issues and much more.

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