Artificial Intelligence

As the volume of public and private video data expands at a rapid rate, with YouTube alone reporting more than 100 videos posted every minute, it becomes increasingly crucial to be able to quickly find specific moments within this growing aggregation of video data.

In collaboration with IMSC, Nevatia and his team address the problem of efficiently locating specific portions within long expanses of video through semantic content extraction and content indexing. To this end, we are developing a finer set of query terms based on new detection and tracking methodologies. The resulting representations can then be used for extracting contents that will allow understanding of the events occurring in the scene. Such automated tools will be essential for analysts in the intelligence community to cope with and make effective use of the vast quantities of video data that are becoming increasingly available.

Janus – Multi Source Event Detection and Collection System for Effective Surveillance of Criminal Activity
Shahabi, Cyrus; Kim, Seon Ho; Nocera, Luciano; Constantinou, Giorgos; Lu, Ying; Cai, Yinghao; Medioni, Gerard; Nevatia, Ramakant; Banaei-Kashani, Farnoush;
Journal of Information Processing Systems, 2014.

Geodec: Enabling Geospatial Decision Making
Cyrus Shahabi, Yao-Yi Chiang, Kelvin Chung, Kai-Chen Huang, Jeff Khoshgozaran-Haghighi, Craig
Knoblock, Sung Chun Lee, Ulrich Neumann, Ram Nevatia, Arjun Rihan, Snehal Thakkar, Suya You
2006 IEEE International Conference on Multimedia and Expo, 2006.