How do you think the new GigE standards will influence the machine vision industry?
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Entranceways, walkways and back doors all seem to have a surveillance camera zooming in on someone. Each step, each movement, each action is caught on tape (or in the case of digital video recorders, or DVRs, in the hard drive). The cameras run 24 hours a day, all without blinking an eye.
But when day turns into night, that is when the camera begins to lose its focus. One of the emerging trends in security and surveillance is night vision, because criminals feel they can break into any facility unseen. "Night vision imaging capability becomes a key part of any security and surveillance now," says James Zahn, president and CEO of Cantronic Systems Inc. (Coquitlam, BC, Canada). "The need for night vision surveillance and security products has grown significantly following 9/11."
John Clark, vice president of commercial technology development for ObjectVideo (Reston, VA), says the use of video surveillance cameras is on the rise. "What has changed in the last two to three years is the sophistication of how that video is being used," he said. "It is no longer considered enough to backhaul camera feeds to a central monitoring port and record the information for a few weeks. New technologies are being introduced in the encoding, transmission, management and analysis of that video information. Compression techniques continue to get attention, wired and wireless networking technologies that were once dedicated to Internet and intranet traffic flow are now being engineered to include surveillance video, and more and more deployments are engineering video content analysis into their requirements."
ObjectVideo worked with Texas Instruments (Dallas, TX) to launch its video content analysis algorithms to run on TI's DM64x digital media processors, enabling analytical capabilities to reside directly on video cameras, DVRs, network encoders and other video management platforms. This would diminish the need for a centralized server and the hardware requirements for an intelligent security system; this, in turn, reduces system requirements and the overall cost of ownership for the end-user.
"As new problems are identified, more algorithms will emerge, and increased pressure will be placed on rapid commercialization," Clark says. "In addition, these new features must be economically within the reach of mass markets for them to be readily adopted. Thus, part of the success of increased sophistication of image analytics relies on increased power of the host hardware and riding the cost curve down."