Edizione	[1st ed. 2013.]
Pubbl/distr/stampa	Heidelberg [Germany] : , : Springer, , 2013
Descrizione fisica	1 online resource (ix, 192 pages) : illustrations (some color)
Disciplina	006.3
Collana	Gale eBooks
Soggetto topico	Electronic surveillance Computer science Multimedia systems Artificial intelligence Computer vision
ISBN	3-642-41512-1
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Chap. 1 - Intelligent Video Surveillance as a Service -- Chap. 2 - A Literature Review on Video Analysis of Crowded Scenes -- Chap. 3 - Privacy and Security in Video Surveillance -- Chap. 4 - Object Video Streams: A Framework for Preserving Privacy in Video Surveillance -- Chap. 5 - Surveillance Privacy Protection -- Chap. 6 - RFID Localization Improved by Motion Segmentation in Multimedia Surveillance Systems -- Chap. 7 - A Framework For Object Tracking Using Visual Saliency Information -- Chap. 8 - Scene Understanding Via Multiresolution Disparity Map in PTZ Camera Network -- Chap. 9 - Performance Evaluation in Video-Surveillance Systems: the EventVideo Project Evaluation Protocols.
Record Nr.	UNINA-9910437601303321

Autore	Aghajan Hamid K
Edizione	[1st edition]
Pubbl/distr/stampa	Amsterdam ; ; Boston, : Elsevier, AP, c2009
Descrizione fisica	1 online resource (623 p.)
Disciplina	621.38834 621.38928
Altri autori (Persone)	AghajanHamid K CavallaroAndrea
Soggetto topico	Sensor networks Cameras Computer vision Computer networks Signal processing - Digital techniques Electronic surveillance Video recording
ISBN	9786612120671 9781282120679 1282120670 9780080878003 0080878008
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Front Cover; Multi-Camera Networks; Copyright Page; Table of Contents; Foreword; Preface; Part 1: Multi-Camera Calibration and Topology; Chapter 1. Multi-View Geometry for Camera Networks; 1.1 Introduction; 1.2 Image Formation; 1.2.1 Perspective Projection; 1.2.2 Camera Matrices; 1.2.3 Estimating the Camera Matrix; 1.3 Two-Camera Geometry; 1.3.1 Epipolar Geometry and Its Estimation; 1.3.2 Relating the Fundamental Matrix to the Camera Matrices; 1.3.3 Estimating the Fundamental Matrix; 1.4 Projective Transformations; 1.4.1 Estimating Projective Transformations 1.4.2 Rectifying Projective Transformations1.5 Feature Detection and Matching; 1.6 Multi-Camera Geometry; 1.6.1 Affine Reconstruction; 1.6.2 Projective Reconstruction; 1.6.3 Metric Reconstruction; 1.6.4 Bundle Adjustment; 1.7 Conclusions; 1.7.1 Resources; References; Chapter 2. Multi-View Calibration, Synchronization, and Dynamic Scene Reconstruction; 2.1 Introduction; 2.2 Camera Network Calibration and Synchronization; 2.2.1 Epipolar Geometry from Dynamic Silhouettes; 2.2.2 Related Work; 2.2.3 Camera Network Calibration; 2.2.4 Computing the Metric Reconstruction 2.2.5 Camera Network Synchronization2.2.6 Results; 2.3 Dynamic Scene Reconstruction from Silhouette Cues; 2.3.1 Related Work; 2.3.2 Probabilistic Framework; 2.3.3 Automatic Learning and Tracking; 2.3.4 Results and Evaluation; 2.4 Conclusions; References; Chapter 3. Actuation-Assisted Localization of Distributed Camera Sensor Networks; 3.1 Introduction; 3.2 Methodology; 3.2.1 Base Triangle; 3.2.2 Large-Scale Networks; 3.2.3 Bundle Adjustment Refinement; 3.3 Actuation Planning; 3.3.1 Actuation Strategies; 3.3.2 Actuation Termination Rules; 3.4 System Description; 3.4.1 Actuated Camera Platform 3.4.2 Optical Communication Beaconing3.4.3 Network Architecture; 3.5 Evaluation; 3.5.1 Localization Accuracy; 3.5.2 Node Density; 3.5.3 Latency; 3.6 Conclusions; References; Chapter 4. Building an Algebraic Topological Model of Wireless Camera Networks; 4.1 Introduction; 4.2 Mathematical Background; 4.2.1 Simplicial Homology; 4.2.2 Example; 4.2.3 Cech Theorem; 4.3 The Camera and the Environment Models; 4.4 The CN-Complex; 4.5 Recovering Topology: 2D Case; 4.5.1 Algorithms; 4.5.2 Simulation in 2D; 4.6 Recovering Topology: 2.5D Case; 4.6.1 Mapping from 2.5D to 2D; 4.6.2 Building the CN-Complex 4.6.3 Experimentation4.7 Conclusions; References; Chapter 5. Optimal Placement of Multiple Visual Sensors; 5.1 Introduction; 5.1.1 Related Work; 5.1.2 Organization; 5.2 Problem Formulation; 5.2.1 Definitions; 5.2.2 Problem Statements; 5.2.3 Modeling a Camera's Field of View; 5.2.4 Modeling Space; 5.3 Approaches; 5.3.1 Exact Algorithms; 5.3.2 Heuristics; 5.3.3 Random Selection and Placement; 5.4 Experiments; 5.4.1 Comparison of Approaches; 5.4.2 Complex Space Examples; 5.5 Possible Extensions; 5.6 Conclusions; References; Chapter 6. Optimal Visual Sensor Network Configuration; 6.1 Introduction 6.1.1 Organization
Record Nr.	UNINA-9911006626303321

Edizione	[1st ed. 2014.]
Pubbl/distr/stampa	Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica	1 online resource (X, 159 p. 67 illus.)
Disciplina	006.42
Collana	Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico	Optical data processing Pattern recognition Artificial intelligence Computer graphics Application software Algorithms Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Computer Graphics Information Systems Applications (incl. Internet) Algorithm Analysis and Problem Complexity
ISBN	3-319-12811-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Introduction -- The Applications of Video Analytics in Media Planning, Trade and Shopper Marketing -- Demographics -- Pervasive Retail Strategy using a Low-Cost Free Gaze Estimation System -- Face Re-Identification for Digital Signage Applications -- Evaluation of LBP and HOG Descriptors for Clothing Attribute Description -- Features descriptors for demographic estimation: a comparative study -- Comparison of Facial Alignment Techniques: with Test Results on Gender Detection Task -- Multi-view Face Detection with One Classifier for Video Analytics Systems -- Part 3 Modelling Consumer Behavior -- Online Audience Measurement System based on Machine Learning Techniques -- Modelling In-Store Consumer Behavior using Machine Learning and Digital Signage Audience Measurement Data -- Shopper Behavior Analysis Based on 3D Situation Awareness Information -- Shopper Analytics: a customer activity recognition system using a distributed RGB-D camera network.
Record Nr.	UNISA-996213646603316

Edizione	[1st ed. 2017.]
Pubbl/distr/stampa	Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica	1 online resource (X, 163 p. 86 illus.)
Disciplina	006.42
Collana	Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico	Optical data processing Computers Artificial intelligence Computer security Special purpose computers Computer Imaging, Vision, Pattern Recognition and Graphics Information Systems and Communication Service Artificial Intelligence Systems and Data Security Special Purpose and Application-Based Systems
ISBN	3-319-56687-3
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Person Re-Identification Dataset with RGB-D Camera in a Top-View Configuration -- Pervasive System for Consumer Behaviour Analysis in Retail Environments -- Estimation of task difficulty and habituation effect while visual manipulation using pupillary response -- Robust Probabilistic Logo Detection in Broadcast Videos for Audience Measurement -- Saliency Prediction for Visual Regions of Interest with Applications in Advertising -- Person Invariant Classification of Subtle Facial Expressions using Coded Movement Direction of Keypoints -- A Two-directional Two-Dimensional PCA Correlation Filter in the Phase Only Spectrum for Face Recognition in Video -- End to End Deep Learning for Single Step Real-time Facial Expression Recognition -- Comparative Study of Human Age Estimation Based on Hand-crafted and Deep Face Features -- Pose-Selective Max Pooling for Measuring Similarity -- Complementing SRCNN by Transformed Self-Exemplars. -Human Head Pose Estimation on SASE database using Random Hough Regression Forests -- Spatio-Temporal Pain Recognition in CNN-based Super-Resolved Facial Images.
Record Nr.	UNISA-996466188803316

Autore	Maggio Emilio
Pubbl/distr/stampa	Chichester, West Sussex, UK ; ; Hoboken, NJ, : Wiley, 2010
Descrizione fisica	1 online resource (294 p.)
Disciplina	621.389/28 621.38928
Altri autori (Persone)	CavallaroAndrea
Soggetto topico	Video surveillance Automatic tracking
ISBN	1-119-95686-2 1-280-76757-X 9786613678348 0-470-97438-9 0-470-97437-0
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	VIDEO TRACKING; Contents; Foreword; About the authors; Preface; Acknowledgements; Notation; Acronyms; 1 What is video tracking?; 2 Applications; 3 Feature extraction; 4 Target representation; 5 Localisation; 6 Fusion; 7 Multi-target management; 8 Context modeling; 9 Performance evaluation; Epilogue; Further reading; Appendix A Comparative results; Index
Record Nr.	UNINA-9910139392003321