Academic Press Group and Crowd Behavior for Computer Vision (Computer Vision and Pattern Recognition)

Product Description Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation of people. Part Two focuses on features and representations with the aim of recognizing the presence of groups and crowds in image and video data. It discusses low level processing methods to individuate when and where a group or crowd is placed in the scene, spanning from the use of people detectors toward more ad-hoc strategies to individuate group and crowd formations. Part Three discusses methods for analyzing the behavior of groups and the crowd once they have been detected, showing how to extract semantic information, predicting/tracking the movement of a group, the formation or disaggregation of a group/crowd and the identification of different kinds of groups/crowds depending on their behavior. The final section focuses on identifying and promoting datasets for group/crowd analysis and modeling, presenting and discussing metrics for evaluating the pros and cons of the various models and methods. This book gives computer vision researcher techniques for segmentation and grouping, tracking and reasoning for solving group and crowd modeling and analysis, as well as more general problems in computer vision and machine learning. Review Presents group and crowd analysis and modeling techniques, combining insights from social science with technological methods From the Back Cover Group and Crowd Behavior for Computer Vision takes a multidisciplinary perspective to solving the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. Coverage includes: Detecting a group or a crowd in an image/video, starting from low-level features to the adoption of high-level methods for effectively analyzing and understanding group/crowd behavior Advanced techniques of segmentation and grouping, tracking and reasoning Benchmarks that are publicly available in the literature, their peculiarities and limitations This book gives researchers in computer vision a comprehensive overview of the state-of-the-art in group and crowd analysis and modeling, including a social (psychological) perspective, making it a valuable resource for those wanting to enter and those already working within this field. Features Covers the topic of modeling and analysis of groups and crowd in computer vision Offers a unique cross-disciplinary perspective on group and crowd modeling using anthropological theories translated into computer vision algorithms, showing how groups and crowd behavior analysis can benefit from the findings of social science Focuses on group and crowd analysis metrics Shows how real industrial systems can tackle the problem of analyzing groups and crowds About the Author Full professor at the University of Verona, Italy, and director of the PAVIS (Pattern Analysis and Computer Vision) department at the Istituto Italiano di Tecnologia. He took the Laurea degree in Electronic Engineering in 1989 and a Ph.D. in Electronic Engineering and Computer Science in 1993 at the University of Genova, Italy. His main research interests include: computer vision and pattern recognition/machine learning, in particular, probabilistic techniques for image and video processing, with applications on video surveillance, biomedical image analysis and bioinformatics.