Accession Number:

ADA636907

Title:

Activity Recognition in Social Media

Descriptive Note:

Final rept. 12 Aug 2013-30 Sep 2015

Corporate Author:

INDIAN INST OF TECHNOLOGY BOMBAY (INDIA)

Personal Author(s):

• Chaudhuri, Subhasis

Report Date:

2015-12-29

Pagination or Media Count:

15.0

Abstract:

A novel approach to analyze crowd behavior at various levels of granularity - individual, group and global. We first model the collective motion of the agents present in the scene by a first order dynamical system. The model learns the spatio-temporal interaction pattern of the crowd which is further analyzed for group detection. The groups are identifiable from the eigenvectors of the interaction matrix of the model and can be recovered by employing a variant of spectral clustering on the eigenvectors. We show that while eigenvectors detect groups, the eigenvalues characterize various group activities such as stationary, walking, splitting and approaching. Finally we classify a crowd video in one of the eight categories by employing a random forest. As an application, the model is used to predict personal space violation.

Descriptors:

• *GROUP DYNAMICS
• *MATHEMATICAL MODELS
• INTERACTIONS
• MULTIAGENT SYSTEMS

Subject Categories:

• Sociology and Law
• Psychology
• Operations Research
• Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE