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Adaptive, Automated Real-time Event/Target Detection using Supervised Learning

Award Information

Agency:
Department of Defense
Branch:
N/A
Award ID:
Program Year/Program:
2012 / SBIR
Agency Tracking Number:
N121-017-0198
Solicitation Year:
2012
Solicitation Topic Code:
N121-017
Solicitation Number:
2012.1
Small Business Information
Kitware Inc.
28 Corporate Drive Clifton Park, NY 12065-8688
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2012
Title: Adaptive, Automated Real-time Event/Target Detection using Supervised Learning
Agency: DOD
Contract: N68335-12-C-0187
Award Amount: $79,994.00
 

Abstract:

Automatic event and activity recognition from stream video and video archive can greatly enhance the effectiveness and efficiency of motion imagery analyst by filtering out the most relevant and timely content from a huge amount of video data through query video clips. Building on our DARPA VIRAT program to detect various events, such as vehicle starting, stopping, turning, U-turning, person running and so on, we propose to improve novel event detection by leveraging existing event modules to build the new model through semi-supervised learning and label expansion. The proposed approach will allow the user to annotate just a few training samples, and it will automatically label additional data based on other, existing event models, thus improving the new model over one built just on the user provided samples. We also propose to explore a novel multi-way interaction descriptor based on disjoint information that will be able to describe multi-entity events, and will improve the performance of single entity events by jointly using multiple features.

Principal Investigator:

Harry Sun
Senior Research Engineer
(518) 836-2192
harry.sun@kitware.com

Business Contact:

Vicki Rafferty
Contracts Administrator
(518) 881-4401
vicki.rafferty@kitware.com
Small Business Information at Submission:

Kitware
28 Corporate Drive Clifton Park, NY -

EIN/Tax ID: 141802694
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No