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πŸ“

Video Analytics for Business Intelligence

✍ Scribed by Fatih Porikli, Alper Yilmaz (auth.), Caifeng Shan, Fatih Porikli, Tao Xiang, Shaogang Gong (eds.)


Publisher
Springer-Verlag Berlin Heidelberg
Year
2012
Tongue
English
Leaves
373
Series
Studies in Computational Intelligence 409
Edition
1
Category
Library

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✦ Synopsis


Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice.

✦ Table of Contents


Front Matter....Pages 1-10
Front Matter....Pages 1-1
Object Detection and Tracking....Pages 3-41
Auto-calibration of Non-overlapping Multi-camera CCTV Systems....Pages 43-67
Fast Approximate Nearest Neighbor Methods for Example-Based Video Search....Pages 69-97
Front Matter....Pages 99-99
Human Age Estimation and Sex Classification....Pages 101-131
People Counter: Counting of Mostly Static People in Indoor Conditions....Pages 133-159
Scene Invariant Crowd Counting and Crowd Occupancy Analysis....Pages 161-198
Identifying Customer Behaviour and Dwell Time Using Soft Biometrics....Pages 199-238
Front Matter....Pages 239-239
Automatic Activity Profile Generation from Detected Functional Regions for Video Scene Analysis....Pages 241-269
Analyzing Groups: A Social Signaling Perspective....Pages 271-305
Front Matter....Pages 307-307
Video Analytics for Business Intelligence....Pages 309-354
Design and Validation of a System for People Queue Statistics Estimation....Pages 355-373
Back Matter....Pages 0--1

✦ Subjects


Computational Intelligence; Artificial Intelligence (incl. Robotics); Business Information Systems; Image Processing and Computer Vision


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