Computer Vision: Challenges, Trends, and Opportunities: Chapman & Hall/CRC Computer Vision
Editat de Md Atiqur Rahman Ahad, Upal Mahbub, Matthew Turk, Richard Hartleyen Limba Engleză Hardback – 30 iul 2024
Complementar volumului Leveraging Computer Vision to Biometric Applications, care se concentrează strict pe algoritmi de învățare profundă pentru identificare, acest volum extinde analiza către un spectru vast de provocări socio-tehnice și industriale. Observăm o abordare pragmatică a vederii artificiale, unde accentul nu cade doar pe succesul algoritmilor, ci și pe limitările lor critice, cum ar fi cauzele variațiilor demografice în acuratețea recunoașterii faciale sau obstacolele întâmpinate în implementările industriale.
În contextul operei editorilor, Computer Vision reprezintă o sinteză matură ce rafinează temele explorate anterior în Human Activity and Behavior Analysis. Dacă lucrările precedente se concentrau pe recunoașterea acțiunilor umane, volumul de față integrează aceste concepte în ecosisteme mai complexe, precum reabilitarea la domiciliu după un accident vascular cerebral sau analiza sportivă. Structura cărții facilitează o progresie logică de la bazele AI-ului bazat pe date (Data-Driven AI) către aplicații specializate în criminalistică digitală și neuromorphic computing. Remarcăm prezența celor 308 ilustrații care susțin explicațiile tehnice, oferind o claritate necesară în înțelegerea arhitecturilor de tip U-Net pentru segmentarea imaginilor medicale.
Spre deosebire de EMERG TOPIC IN COMP VISION & ITS APPL, care pune un accent deosebit pe viziunea robotică și marină, lucrarea de față prioritizează intersecția dintre computer vision și etica datelor, oferind perspective valoroase despre cum „știe AI-ul ce ai făcut astă vară” în contextul criminalisticii. Este o resursă tehnică ce documentează stadiul actual al tehnologiei (state-of-the-art), fiind esențială pentru înțelegerea direcțiilor viitoare în XR (Extended Reality) și vehicule autonome.
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Specificații
ISBN-10: 1032317051
Pagini: 360
Ilustrații: 308
Dimensiuni: 210 x 280 x 24 mm
Greutate: 1.16 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Computer Vision
Locul publicării:Boca Raton, United States
Public țintă
Postgraduate and ProfessionalDe ce să citești această carte
Recomandăm această carte profesioniștilor și cercetătorilor care au nevoie de o imagine de ansamblu aplicată asupra vederii artificiale moderne. Cititorul câștigă acces la soluții concrete pentru provocări de nișă, de la biometrie „soft” la procesarea imaginilor medicale, beneficiind de expertiza unor lideri din industrie și mediul academic. Este un ghid tehnic riguros pentru optimizarea sistemelor de viziune în medii de producție reale.
Despre autor
Editorii volumului sunt figuri proeminente în comunitatea științifică internațională. Md Atiqur Rahman Ahad este recunoscut pentru lucrările sale extensive în analiza comportamentului uman și tehnologii de asistență medicală, publicând anterior titluri de referință precum Activity, Behavior, and Healthcare Computing. Alături de el, Matthew Turk și Richard Hartley aduc o expertiză vastă în algoritmi fundamentali de viziune computerizată și geometrie multi-view. Colectivul de autori reunește specialiști de la instituții de prestigiu și lideri din sectorul R&D, asigurând un echilibru între rigoarea teoretică și aplicabilitatea industrială sub egida editurii CRC Press.
Descriere scurtă
This book highlights various core challenges as well as solutions by leading researchers in the field. It covers such important topics as data-driven AI, biometrics, digital forensics, healthcare, robotics, entertainment and XR, autonomous driving, sports analytics, and neuromorphic computing, covering both academic and industry R&D perspectives. Providing a mix of breadth and depth, this book will have an impact across the fields of computer vision, imaging, and AI.
Computer Vision: Challenges, Trends, and Opportunities covers timely and important aspects of computer vision and its applications, highlighting the challenges ahead and providing a range of perspectives from top researchers around the world. A substantial compilation of ideas and state-of-the-art solutions, it will be of great benefit to students, researchers, and industry practitioners.
Cuprins
1 Some Challenges and Solutions in Data-Driven AI
Rama Chellappa, Jiang Liu, Chun Pong Lau, and Prithviraj Dhar
2 Challenges of Computer Vision Research from an Industry Perspective
Fatih Porikli
3 Soft Biometrics for Human Identication
Mark S. Nixon and Emad Sami Jaha
4 Exploring Causes of Demographic Variations in Face Recognition Accuracy
Gabriella Pangelinan, K.S. Krishnapriya, Vitor Albiero, Grace Bezold, Kai Zhang, Kushal Vangara,
Michael C. King, and Kevin W. Bowyer
5 AI Knows What You Did Last Summer: Applications in Digital Forensics
Jing Yang, José Nascimento, Gabriel Bertocco, Antonio Theophilo, Rafael Padilha, Aurea Soriano-Vargas, Fernanda A. Andaló, and Anderson Rocha
6 Advances in Computer Vision for Home-Based Stroke Rehabilitation
7 U-Net-based Medical Image Segmentation: A Comparative Analysis and Future Trends
Sidike Paheding, Abel A. Reyes-Angulo, and Mohammad S. Alam
8 Robot-Mediated Assistance: Opportunities and Challenges in Computer Vision and Human—Robot Interaction
Md Alimoor Reza and Syed Masum Billah
9 Computer Vision Applications in Underwater Robotics and Oceanography
Md Jahidul Islam, Alberto Quattrini Li, Yogesh A Girdhar, and Ioannis Rekleitis
10 Applications of Computer Vision in Entertainment and Media Industry
Mahmudul Hasan, Kishan Shamsundar Athrey, Arfeen Khalid, Danfeng Xie, Ehsan Younessian, and Tony Braskich
11 Quality Assessment in Media and Entertainment: Challenges and Trends
Abhinau K. Venkataramanan, Zaixi Shang, Joshua P. Ebenezer, Meixu Chen, Zhengzhong Tu, and Alan C. Bovik
12 Immersive User Experiences: Trends and Challenges of Using XR Technologies
Vasudev Bhaskaran and Upal Mahbub
Kowshik Thopalli, Niccolo Meniconi, Tamim Ahmed, Sai Krishna Yeshala, Aisling Kelliher, Thanassis Rikakis, and Pavan Turaga
13 Multi-camera Bird's Eye View Perception for Autonomous Driving
David Unger, Nikhil Gosala, Varun Ravi Kumar, Shubhankar Borse, Abhinav Valada, and Senthil Yogamani
14 The (Computer) Vision of Sports: Recent Trends in Research and Commercial Systems for Sport Analytics
Rikke Gade, Michele Merler, Graham Thomas, and Thomas B. Moeslund
15 Spike-Based Neuromorphic Computing for Next-Generation Computer Vision
Md Sakib Hasan, Catherine D. Schuman, Zhongyang Zhang, Tauhidur Rahman, and Garrett S. Rose
Recenzii
Notă biografică
Upal Mahbub, Ph.D., Senior Member IEEE, is currently working as a Senior Engineer at the Multimedia R&D Lab at Qualcomm Technologies Inc., San Diego, California, USA. He received his Ph.D. (2018) and an M.Sc. (2017) degrees in Electrical and Computer Engineering from the University of Maryland College Park. Before joining the Ph.D. program, Dr. Mahbub was an Assistant Professor at the Dept. of EEE, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh. Upal Mahbub is the recipient of the best paper award at IEEE UEMCON 2016, the best poster award at BTAS 2016, the best paper award at ICCIT 2011, and a distinguished graduate fellowship from the A. James Clark School of Engineering at the University of Maryland. He has published over thirty articles in international conferences and prestigious journals, recently published an edited book entitled “Contactless Human Activity Analysis”, served as editor in international journals (guest editor of PRL special issue AHAAGR 2021, associate editor of IJCVSP), presented his research at numerous conferences, and served in the technical and/or program committees of ICIEV (2012-2021), IVPR (track chair 202, program chair 2021), ICECE (2010 & 2012), and ABC (2019, 2020, 2021).
Matthew Turk, Ph.D., Fellow, IEEE; Fellow, Fellow IAPR, is the President of the Toyota Technological Institute at Chicago (TTIC) and an emeritus professor in computer science at the University of California, Santa Barbara, where he co-directed the UCSB Four Eyes Lab. He received a PhD from the Massachusetts Institute of Technology. He has worked at Martin Marietta Aerospace, LIFIA/ENSIMAG (Grenoble, France), Teleos Research, and Microsoft Research, where he was a founder of the Vision Technology Group. He has served as General or Program Chair of several major conferences, including the ACM Multimedia Conference, the IEEE Conference on Automatic Face and Gesture Recognition, the ACM International Conference on Multimodal Interaction, the IEEE Conference on Computer Vision and Pattern Recognition, and the IEEE Winter Conference on Applications of Computer Vision. He co-founded an augmented reality startup company in 2014 that was acquired by PTC Vuforia in 2016. Dr. Turk has received several best paper awards, and he is an ACM Fellow, an IEEE Fellow, an IAPR Fellow, and the recipient of the 2011-2012 Fulbright-Nokia Distinguished Chair in Information and Communications Technologies.
Richard Hartley, Ph.D., Fellow, IEEE; Fellow, Australian Academy of Science; Fellow, Australian Mathematical Society, is a member of the computer vision group in the Department of Information Engineering, at the Australian National University, where he has been since January 2001. He did his doctoral research in Mathematics at the University of Toronto, Canada in 1976. He also received an MSc in Mathematics from the same university in 1972 and another MSc in Computer Science from Stanford University in 1985. Dr. Hartley worked at the General Electric Research and Development Center from 1985 to 2001. During the period 1985-1988, he was involved in the design and implementation of Computer-Aided Design tools for electronic design and created a very successful design system called the Parsifal Silicon Compiler. In 1991 he was awarded GE's Dushman Award for this work.