Research Lab Advances Intelligent Video

The two greatest forces driving the security industry are money and technology. Saving as much of the former as possible while advancing the latter is the delicate balance security directors and manufacturers serving the industry must strike. The...


The two greatest forces driving the security industry are money and technology. Saving as much of the former as possible while advancing the latter is the delicate balance security directors and manufacturers serving the industry must strike. The fulcrum of the scale is the industry’s reliance on robust R&D that can feed the constant demand for new technologies in cost-effective ways.

A number of labs and universities around the world conduct R&D in an effort to bring high-technology solutions to bear on the challenges of the security marketplace. One such facility is MERL, Mitsubishi Electric Research Laboratory, owned by Mitsubishi Electric. Located in Cambridge, MA, MERL conducts application-motivated basic research in computer and communications technologies. Although it can leverage the size and power of its corporate parent, it remains independent enough to be flexible.

Heavily involved in the global R&D community and active in the various standards processes, the lab maintains long-standing cooperative relationships with a number of research universities including MIT, CMU, Georgia Tech, Princeton, Columbia, University of Paris, Dublin City University, ETH Zurich, and the City University of London. The goals of MERL’s activities are to publish papers, file patents and create prototypes for the company and to take the technology to the groups within the larger company that can benefit from that work.

From Data to Video
Research efforts at MERL focus on five technology areas: computer vision, digital communications, digital video, off-the-desktop interaction and display (interface concepts), and sensor and data systems. Each of these areas is split up into two parts: the research lab, where the blue-sky conceptualization occurs, and the tech lab, where the concepts are refined into technology.

“From the research level, we then develop software libraries which the different divisions can evaluate for use in their products,” said Jay Thornton, computer vision applications group manager. The interested divisions plug the software into their prototypes, then test it. “They will then get back to us and tell us where they need improvements before it’s viable for the marketplace.”

Most of the research and resulting products that impact the security industry emanate from within the computer vision section. This includes 3-D face recognition, audio-visual event detection, camera network calibration and object detection and tracking. The security marketplace has recently gravitated toward human movement and behavior tracking, and MERL has made strides here, according to Dr. Kent Wittenburg, the lab’s vice president and director. “The lab has extended its efforts in tracking objects from background subtraction to active object detection techniques that happen in the foreground,” he said. “This extension helps in low-light conditions and also when the camera is moving.”

Face Recognition Research
The face recognition program started at MERL as face detection, in which software would analyze video frame by frame to determine if a face was present. The application for this in a security installation is a situation in which a camera is focused on an area where nobody is supposed to be. If a face is detected, the system will alarm the operator that somebody is there.

Through feedback from the divisions and continuing research using advanced machine learning techniques, that technology advanced to include face classification, wherein the software can detect a male or female face and differentiate between a happy or sad expression, for example. The next step is face recognition of individual people, an area that has proved elusive.

“The face recognition software library is currently in its fourth iteration,” explained Thornton, “because we often get feedback from the product divisions to improve performance in real-world conditions.”

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