Date: Mar 20, 2011 Source: In-Q-Tel (
click here to go to the source)
Signal Innovations Group, Inc. (SIG), a leader in signal and image processing for defense and security, today announced a strategic investment and technology development agreement with In-Q-Tel, the independent strategic investment firm that identifies innovative technology solutions to support the missions of the U.S. Intelligence Community.
This strategic partnership between SIG and IQT will extend SIG's Intelligence, Surveillance, and Reconnaissance (ISR) technology development and provide new opportunities for SIG's product deployment. SIG's unique probabilistic framework sifts relevant data from the overwhelming volume of raw sensor data (pixels) to realize the full information potential from video systems. The company's data products include stabilized and georegistered imagery, vehicle and dismount tracks, traffic and behavior models, and analyst-aided-cueing for improved accuracy.
"Partnering with IQT helps us understand the system requirements and end-user needs for demanding video applications for security and intelligence," said Dr. Paul Runkle, CEO of SIG. "The insight provided by IQT's customers helps us drive technology innovation and product design for both commercial and government applications."
"SIG is a critical addition to our strategic investment portfolio and we are impressed with this technology's applicability to the challenges facing the Intelligence Community," said William Strecker, Executive Vice President and CTO at IQT. "SIG's video analytics technology offers unparalleled capabilities for extracting and representing relevant information in commercial and government video data."
Specific terms of the agreement were not disclosed.
About SIG
SIG is an emerging leader in signal, image, and video analytics for government and commercial applications. SIG's novel technology enables vast improvements in extracting relevant information from signals and imagery and making accurate decisions using this data. SIG's technology can utilize feedback from end-users to help the algorithms gain the benefit from human-aided decisions.
