Mr. George M. Roberts Profile

George M. Roberts

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Proceedings Article | 16 April 2008 Paper

Target activated frame capture

G. Marlon Roberts, James Fitzgerald, Michael McCormack, Robert Steadman

Proceedings Volume 6963, 69630Z (2008) https://doi.org/10.1117/12.783045

KEYWORDS: Target detection, Detection and tracking algorithms, Cameras, Edge detection, Motion detection, Sensors, Video, Composites, Intelligence systems, Surveillance

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Over the past decade, technological advances have enabled the use of increasingly intelligent systems for battlefield surveillance. These systems are triggered by a combination of external devices including acoustic and seismic sensors. Such products are mainly used to detect vehicles and personnel. These systems often use infra-red imagery to record environmental information, but Textron Defense Systems' Terrain Commander is one of a small number of systems which analyze these images for the presence of targets. The Terrain Commander combines acoustic, infrared, magnetic, seismic, and visible spectrum sensors to detect nearby targets in military scenarios. When targets are detected by these sensors, the cameras are triggered and images are captured in the infrared and visible spectrum. In this paper we discuss a method through which such systems can perform target tracking in order to record and transmit only the most pertinent surveillance images. This saves bandwidth which is crucial because these systems often use communication systems with throughputs below 2400bps. This method is expected to be executable on low-power processors at frame rates exceeding 10HZ. We accomplish this by applying target activated frame capture algorithms to infra-red video data. The target activated frame capture algorithms combine edge detection and motion detection to determine the best frames to be transmitted to the end user. This keeps power consumption and bandwidth requirements low. Finally, the results of the algorithm are analyzed.

Proceedings Article | 11 May 2007 Paper

UGS video target detection and discrimination

G. Marlon Roberts, James Fitzgerald, Michael McCormack, Robert Steadman, Joseph Vitale

Proceedings Volume 6562, 65620J (2007) https://doi.org/10.1117/12.736101

KEYWORDS: Detection and tracking algorithms, Target detection, Image processing, Sensors, Video processing, Video, Infrared imaging, Unattended ground sensors, Acoustics, Video surveillance

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This project focuses on developing electro-optic algorithms which rank images by their likelihood of containing vehicles and people. These algorithms have been applied to images obtained from Textron's Terrain Commander 2 (TC2) Unattended Ground Sensor system. The TC2 is a multi-sensor surveillance system used in military applications. It combines infrared, acoustic, seismic, magnetic, and electro-optic sensors to detect nearby targets. When targets are detected by the seismic and acoustic sensors, the system is triggered and images are taken in the visible and infrared spectrum. The original Terrain Commander system occasionally captured and transmitted an excessive number of images, sometimes triggered by undesirable targets such as swaying trees. This wasted communications bandwidth, increased power consumption, and resulted in a large amount of end-user time being spent evaluating unimportant images. The algorithms discussed here help alleviate these problems. These algorithms are currently optimized for infra-red images, which give the best visibility in a wide range of environments, but could be adapted to visible imagery as well. It is important that the algorithms be robust, with minimal dependency on user input. They should be effective when tracking varying numbers of targets of different sizes and orientations, despite the low resolutions of the images used. Most importantly, the algorithms must be appropriate for implementation on a low-power processor in real time. This would enable us to maintain frame rates of 2 Hz for effective surveillance operations. Throughout our project we have implemented several algorithms, and used an appropriate methodology to quantitatively compare their performance. They are discussed in this paper.

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