Short description:

With the vast development of Internet and media technologies, intelligent video event analysis is a gradually growing field of research in recent decades. Significant challenges include how to handle background clutter, occlusions, as well as interactions. Another difficulty is the lacking of widely accepted definition of event in the literature. Though the research achievement is still far from its promise, steady progress has been made in past years. This book collects a set of selected contributions in this area from international experts including leading academic researchers, and industrial practitioners. It presents the latest advances of intelligent video event analysis in both theoretical and application viewpoints.

Topics and features:

?         - Addresses the concept of events by introducing a double view of understanding meaningful events in gesture based interaction

?         - Investigates motion segmentation based on the subspace technique by incorporating the cues from the neighbourhood of intensity edges of images

?         - Provides the state of theart techniques on human action description, and recognition based on 3D spatial temporal features

?         - Presents efficient object localization and detection approaches in challenging scenes

?         - Describes motion analysis techniques in various applications including sports videos, household environment, and surveillance videos 

It provides researchers and practitioners a rich resource for future research directions and successful practice. It could also serve as a reference tool and handbook for researchers in a number of applications including visual surveillance, human-computer interaction, and video search and indexing, etc. Graduate students working on video analysis in various disciplines such as computer vision, pattern recognition, information security, artificial intelligence will also find it useful.

Long description:

With the vast development of Internet capacity and speed, as well as wide adop- tion of media technologies in people?s daily life, a large amount of videos have been surging, and need to be efficiently processed or organized based on interest. The human visual perception system could, without difficulty, interpret and r- ognize thousands of events in videos, despite high level of video object clutters, different types of scene context, variability of motion scales, appearance changes, occlusions and object interactions. For a computer vision system, it has been be very challenging to achieve automatic video event understanding for decades. Broadly speaking, those challenges include robust detection of events under - tion clutters, event interpretation under complex scenes, multi-level semantic event inference, putting events in context and multiple cameras, event inference from object interactions, etc. In recent years, steady progress has been made towards better models for video event categorisation and recognition, e. g. , from modelling events with bag of spatial temporal features to discovering event context, from detecting events using a single camera to inferring events through a distributed camera network, and from low-level event feature extraction and description to high-level semantic event classification and recognition. Nowadays, text based video retrieval is widely used by commercial search engines. However, it is still very difficult to retrieve or categorise a specific video segment based on their content in a real multimedia system or in surveillance applications.

Table of Contents:

The Understanding of Meaningful Events in Gesture-Based Interaction.- Apply GPCA to Motion Segmentation.- Gait Analysis and Human Motion Tracking.- Spatio-temporal Dynamic Texture Descriptors for Human Motion Recognition.- Efficient Object Localization with Variation-Normalized Gaussianized Vectors.- Fusion of Motion and Appearance for Robust People Detection in Cluttered Scenes.- Understanding Sports Video Using Players Trajectories.- Real-Time Face Recognition from Surveillance Video.- Event Understanding of Human-Object Interaction: Object Movement Detection via Stable Changes.- Survey of Dirac: A Wavelet Based Video Codec for Multiparty Video Conferencing and Broadcasting.- Erratum: Event Understanding of Human-Object Interaction: Object Movement Detection via Stable Changes.