IVA2022: Intelligent Video Analytics: Clustering and Classification Applications |
Submission link | https://easychair.org/conferences/?conf=iva2022 |
Abstract registration deadline | January 15, 2022 |
Submission deadline | February 28, 2022 |
Intelligent Video Analytics: Clustering and Classification Applications
We live in a new era of digital technology where several breakthroughs and applications have been witnessed due to the fusion of machine intelligence with video technology. Smart video cameras are becoming a fashion in business. Video has rich information including meta-data, visual, audio, spatial and temporal data. These data can be analyzed to extract a variety of low-level and high-level features to build predictive computational models using machine-learning algorithms in order to discover interesting patterns, concepts, relations, associations, etc. There are numerous potential applications including human-machine interactions, smart surveillance cameras, smart phones, social media analysis, entertainment industries, video games and sports, medicine and healthcare, intelligent traffic systems, crowd management, biometrics, demographic analysis, intelligent manufacturing, and intelligent instructional systems. In addition to being real time, there are several challenges stimulating research such as handling the dramatic increase in the amount of video data stored and shared from day to day, variable environmental conditions in uncontrolled situations, and application-specific challenges.
It is anticipated that this book will include a review of essential topics and to discuss a collection of emerging methods and potential applications of video data mining and analytics. It will be a useful contribution and can serve as a reference for professionals and as a textbook for graduate students who have interest in intelligent systems, data mining and knowledge discovery, big data analytics, machine learning, neural network and deep learning, video forensics and tamper detection, multimodal biometrics, security and surveillance, manufacturing, social media, sentiment analysis and emotion recognition, gesture and activity recognition, deep fake, information fusion, information retrieval and content management, recommender systems, etc. The field is interdisciplinary spanning computer science, engineering, mathematics, psychology, and cognitive science.
Although there are a number of good book on data mining, computer vision, pattern recognition, machine learning, artificial intelligence, image processing, digital forensics, etc., there is no single book that can integrate these various areas with more focus on multimodality video analytics and recent advances in research and applications.
Examples of potential chapters to be covered in this book include the techniques and applications for:
- Multimodality video analytics
- Gesture and activity recognition
- Sign language recognition
- Face identification and tracking
- Gaze tracking and its applications
- Demographic video analysis
- Gait recognition
- Lip reading
- Real-time additive computing and facial expression recognition
- Driver fatigue detection
- Car license plate recognition
- Autonomous navigation and smart devices
- Loitering and event detection
- Object detection, recognition and tracking
- Crowd monitoring and people count
- Video Analytics for Intelligent Manufacturing
- Traffic monitoring
- Face spoofing recognition
- Video forensics and camera tamper detection
Submission Guidelines
All chapters on topics related to applications of computational intelligence to video analytics are welcomed.
First, submit a brief abstract then submit the full chapter PDF file before the deadlines.
It is preferrable to use latex in preparing your chapter; use the "Krantz book template" on overleaf.
Once your chapter is accepted, you will need to submit all source files for production.
The book will be published by CRC Press.
Editors
- El-Sayed M. El-Alfy, Professor, King Fahd University of Petroleum & Minerals
- George Bebis, Professor and Director, Computer Vision Laboratory, University of Nevada
- Mengchu Zhou, Distinguished Professor and Director, Laboratory for Discrete Event Systems, New Jersey Institute of Technology
Contact
All questions about submissions should be emailed to alfy@kfupm.edu.sa