LEADER 05232nam 2200637 a 450 001 9910141504003321 005 20170815165043.0 010 $a1-118-57785-X 010 $a1-299-18691-2 010 $a1-118-57786-8 010 $a1-118-57793-0 035 $a(CKB)2670000000327567 035 $a(EBL)1120442 035 $a(OCoLC)827207823 035 $a(SSID)ssj0000904813 035 $a(PQKBManifestationID)11494810 035 $a(PQKBTitleCode)TC0000904813 035 $a(PQKBWorkID)10923892 035 $a(PQKB)11603403 035 $a(OCoLC)828890811 035 $a(MiAaPQ)EBC1120442 035 $a(EXLCZ)992670000000327567 100 $a20130301d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aIntelligent video surveillance systems$b[electronic resource] /$fedited by Jean-Yves Dufour 210 $aLondon $cISTE ;$aHoboken, N.J. $cWiley$d2013 215 $a1 online resource (342 p.) 225 0 $aNetworks and telecommunications series 300 $aDescription based upon print version of record. 311 $a1-84821-433-2 320 $aIncludes bibliographical references and index. 327 $aTitle Page; Contents; Introduction; Chapter 1. Image Processing: Overview and Perspectives; 1.1. Half a century ago; 1.2. The use of images; 1.3. Strengths and weaknesses of image processing; 1.3.1. What are these theoretical problems that image processing has been unable to overcome?; 1.3.2. What are the problems that image processing has overcome?; 1.4. What is left for the future?; 1.5. Bibliography; Chapter 2. Focus on Railway Transport; 2.1. Introduction; 2.2. Surveillance of railway infrastructures; 2.2.1. Needs analysis; 2.2.2. Which architectures? 327 $a2.2.3. Detection and analysis of complex events2.2.4. Surveillance of outside infrastructures; 2.3. Onboard surveillance; 2.3.1. Surveillance of buses; 2.3.2. Applications to railway transport; 2.4. Conclusion; 2.5. Bibliography; Chapter 3. A Posteriori Analysis for Investigative Purposes; 3.1. Introduction; 3.2. Requirements in tools for assisted investigation; 3.2.1. Prevention and security; 3.2.2. Information gathering; 3.2.3. Inquiry; 3.3. Collection and storage of data; 3.3.1. Requirements in terms of standardization; 3.3.2. Attempts at standardization (AFNOR and ISO) 327 $a3.4. Exploitation of the data3.4.1. Content-based indexing; 3.4.2. Assisted investigation tools; 3.5. Conclusion; 3.6. Bibliography; Chapter 4. Video Surveillance Cameras; 4.1. Introduction; 4.2. Constraints; 4.2.1. Financial constraints; 4.2.2. Environmental constraints; 4.3. Nature of the information captured; 4.3.1. Spectral bands; 4.3.2. 3D or "2D + Z" imaging; 4.4. Video formats; 4.5. Technologies; 4.6. Interfaces: from analog to IP; 4.6.1. From analog to digital; 4.6.2. The advent of IP; 4.6.3. Standards; 4.7. Smart cameras; 4.8. Conclusion; 4.9. Bibliography 327 $aChapter 5. Video Compression Formats5.1. Introduction; 5.2. Video formats; 5.2.1. Analog video signals; 5.2.2. Digital video: standard definition; 5.2.3. High definition; 5.2.4. The CIF group of formats; 5.3. Principles of video compression; 5.3.1. Spatial redundancy; 5.3.2. Temporal redundancy; 5.4. Compression standards; 5.4.1. MPEG-2; 5.4.2. MPEG-4 Part 2; 5.4.3. MPEG-4 Part 10/H.264 AVC; 5.4.4. MPEG-4 Part 10/H.264 SVC; 5.4.5. Motion JPEG 2000; 5.4.6. Summary of the formats used in video surveillance; 5.5. Conclusion; 5.6. Bibliography 327 $aChapter 6. Compressed Domain Analysis for Fast Activity Detection6.1. Introduction; 6.2. Processing methods; 6.2.1. Use of transformed coefficients in the frequency domain; 6.2.2. Use of motion estimation; 6.2.3. Hybrid approaches; 6.3. Uses of analysis of the compressed domain; 6.3.1. General architecture; 6.3.2. Functions for which compressed domain analysis is reliable; 6.3.3. Limitations; 6.4. Conclusion; 6.5. Acronyms; 6.6. Bibliography; Chapter 7. Detection of Objects of Interest; 7.1. Introduction; 7.2. Moving object detection; 7.2.1. Object detection using background modeling 327 $a7.2.2. Motion-based detection of objects of interest 330 $a Belonging to the wider academic field of computer vision, video analytics has aroused a phenomenal surge of interest since the current millennium. Video analytics is intended to solve the problem of the incapability of exploiting video streams in real time for the purpose of detection or anticipation. It involves analyzing the videos using algorithms that detect and track objects of interest over time and that indicate the presence of events or suspect behavior involving these objects.The aims of this book are to highlight the operational attempts of video analytics, to identify possi 410 0$aISTE 606 $aVideo surveillance 608 $aElectronic books. 615 0$aVideo surveillance. 676 $a621.389/28 676 $a621.38928 701 $aDufour$b Jean-Yves$0969027 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141504003321 996 $aIntelligent video surveillance systems$92201502 997 $aUNINA LEADER 02965nam 2200589Ia 450 001 9910784016203321 005 20230617005026.0 010 $a1-281-86685-7 010 $a9786611866853 010 $a1-86094-724-7 035 $a(CKB)1000000000336350 035 $a(EBL)296150 035 $a(OCoLC)476063693 035 $a(SSID)ssj0000184552 035 $a(PQKBManifestationID)11182380 035 $a(PQKBTitleCode)TC0000184552 035 $a(PQKBWorkID)10200990 035 $a(PQKB)11478922 035 $a(MiAaPQ)EBC296150 035 $a(WSP)00000053 035 $a(Au-PeEL)EBL296150 035 $a(CaPaEBR)ebr10174025 035 $a(CaONFJC)MIL186685 035 $a(EXLCZ)991000000000336350 100 $a20050628d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIterative algorithms for multilayer optimizing control$b[electronic resource] /$fMietek A. Brdys, Piotr Tatjewski 210 $aLondon $cImperial College Press$dc2005 215 $a1 online resource (388 p.) 300 $aDescription based upon print version of record. 311 $a1-86094-514-7 320 $aIncludes bibliographical references (p. 355-362) and index. 327 $aPreface; Notation and Acronyms; Contents; Chapter 1 Multilayer Control; Chapter 2 Optimizing Control Layer; Chapter 3 Iterative Correction with Disturbance Estimation; Chapter 4 Integrated System Optimization and Parameter Estimation (ISOPE); Chapter 5 ISOPE for Problems with Output Constraints; Chapter 6 Iterative Algorithms for Dynamic Optimizing Control; Chapter 7 Optimizing Control of Interconnected Systems; Appendix A Proof of Theorem 4.1; Appendix B Proofs of Theorems 7.1, 7.2 and 7.3; Bibliography; Index 330 $aThe book presents basic structures, concepts and algorithms in the area of multilayer optimizing control of industrial systems, as well as the results of the research that was carried out by the authors over the last two decades. The methodologies and control algorithms are thoroughly illustrated by numerous simulation examples. Also, the applications to several case study examples are presented. These include ethylene distillation column, vaporizer pilot scale plant, styrene distillation line consisting of three columns and industrial furnace pilot scale plant. A temporal decomposition is app 606 $aProcess control$xMathematical models 606 $aSupervisory control systems$xMathematical models 615 0$aProcess control$xMathematical models. 615 0$aSupervisory control systems$xMathematical models. 676 $a620.0011 700 $aBrdys$b Mietek A$01543581 701 $aTatjewski$b Piotr$01543582 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784016203321 996 $aIterative algorithms for multilayer optimizing control$93797131 997 $aUNINA