By Ziyou Xiong, Regunathan Radhakrishnan, Ajay Divakaran, Yong Rui, Thomas S. Huang
Huge volumes of video content material can merely be simply accessed by means of fast looking and retrieval thoughts. developing a video desk of contents (ToC) and video highlights to permit finish clients to sift via all this knowledge and locate what they need, after they wish are crucial. This reference places forth a unified framework to combine those capabilities assisting effective shopping and retrieval of video content material. The authors have built a cohesive solution to create a video desk of contents, video highlights, and video indices that serve to streamline using purposes in purchaser and surveillance video functions. The authors talk about the new release of desk of contents, extraction of highlights, diverse recommendations for audio and video marker acceptance, and indexing with low-level beneficial properties resembling colour, texture, and form. present purposes together with this summarization and perusing know-how also are reviewed. functions corresponding to occasion detection in elevator surveillance, spotlight extraction from activities video, and photograph and video database administration are thought of in the proposed framework. This e-book offers the newest in examine and readers will locate their look for wisdom blissful by way of the breadth of the knowledge coated during this quantity. * deals the most recent in leading edge learn and functions in surveillance and shopper video* Presentation of a unique unified framework aimed toward effectively sifting during the abundance of photos amassed day-by-day at purchasing department shops, airports, and different advertisement amenities* Concisely written by means of prime individuals within the sign processing with step by step guideline in construction video ToC and indices
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Additional resources for A Unified Framework for Video Summarization, Browsing & Retrieval: with Applications to Consumer and Surveillance Video
Take the shot and key frame–based video ToC, for example. It is not uncommon for a modern movie to contain a few thousand shots and key frames. This is evident in Yeung et al. —there are 300 shots in a 15-minute video segment of the movie Terminator 2: Judgment Day, and the movie lasts 139 minutes. Because of the large number of key frames, a simple one-dimensional (1D) sequential presentation of key frames for the underlying video is almost meaningless. More important, people watch the video by its semantic scenes, not the physical shots or key frames.
5 Video Browsing and Retrieval These two functionalities are the ultimate goals of a video access system, and they are closely related to (and built on top of) video representations. e. extracting video mosaics, can be used in video retrieval. On the other hand, the representation techniques for unscripted content are suitable for browsing through highlights-based summarization. 1 VIDEO BROWSING USING TOC-BASED SUMMARY For representation based on sequential key frames, browsing is obviously sequential browsing, scanning from the top-left key frame to the bottom-right key frame.
Existing approaches to scene-level video ToC construction can be classiﬁed into two categories: model based and general purpose. In the model-based approach, an a priori model of a particular application or domain is ﬁrst constructed. This model speciﬁes the scene boundary characteristics, based on which the unstructured video stream can be abstracted into a structured representation. The theoretical framework of this approach has been proposed by Swangberg, Shu, and Jain , and it has been successfully realized in many interesting applications, including news video parsing  and TV soccer program parsing .
A Unified Framework for Video Summarization, Browsing & Retrieval: with Applications to Consumer and Surveillance Video by Ziyou Xiong, Regunathan Radhakrishnan, Ajay Divakaran, Yong Rui, Thomas S. Huang