Realtime pedestrian tracking and prediction in dense crowds / Aniket Bera, David Wolinski, Julien Pettré, Dinesh Manocha. Social interaction in temporary gatherings / Chiara Bassetti -- Group detection and tracking using sociological features / Sebastiano Vascon, Loris Bazzani -- Exploring multitask and transfer learning algorithms for head pose estimation in dynamic multiview scenarios / Elisa Ricci, Yan Yan, Anoop K. Rajagopal, Ramanathan Subramanian, Radu L. Vieriu, Oswald Lanz, Nicu Sebe -- The analysis of high density crowds in videos / Mikel Rodriguez, Josef Sivic, Ivan Laptev -- Tracking millions of humans in crowded spaces / Alexandre Alahi, Vignesh Ramanathan, Li Fei-Fei -- Subject-centric group feature for person reidentification / Li Wei, Shishir K. Shah. -- From groups to leaders and back / Francesco Solera, Simone Calderara, Rita Cucchiara -- Learning to predict human behavior in crowded scenes / Alexandre Alahi, Vignesh Ramanathan, Kratarth Goel, Alexandre Robicquet, Amir A. Sadeghian, Li Fei-Fei, Silvio Savarese -- Deep learning for scene-independent crowd analysis / Xiaogang Wang, Chen-Change Loy -- Physics-inspired models for detecting abnormal behaviors in crowded scenes / Sadegh Mohammadi, Hamed K. Galoogahi, Alessandro Perina, Vittorio Murino -- Activity forecasting / Kris M. Kitani, De-An Huang, Wei-Chiu Ma -- Integrating computer vision algorithms and ontologies for spectator crowd behavior analysis / Davide Conigliaro, Roberta Ferrario, Céline Hudelot, Daniele Porello -- SALSA: a multimodal dataset for the automated analysis of free-standing social interactions / Xavier Alameda-Pineda, Ramanathan Subramanian, Elisa Ricci, Oswald Lanz, Nicu Sebe -- Zero-shot crowd behavior recognition / Xun Xu, Shaogang Gong, Timothy M. Hospedales -- The GRODE metrics / Francesco Setti, Marco Cristani -- Realtime pedestrian tracking and prediction in dense crowds / Aniket Bera, David Wolinski, Julien Pettré, Dinesh Manocha.
Summary:
A multidisciplinary approach to solving the problems of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.