Ed. note: This article has two parts, one from Stretch Inc. on intelligent encoding, and the second from Pixim on camera imaging for surveillance.
One of the fundamental challenges facing anyone attempting to work with video surveillance has always been the size of the video itself. Capturing video produces large amounts of data posing problems both in transportation of the data from one place to another and in subsequent storage. Analog video engineers have for years struggled to hone techniques designed to reduce the size of the captured data without introducing any appreciable loss in quality. Analog systems, however, generally lack the intelligence to effectively tailor these techniques in real time and as such only scratch the surface of what is possible.
Fortunately, with advances in digital video technology, a new set of real time tools can be brought to bear on the video stream. Software configurable processors targeted at video applications are allowing closer coupling between the intelligence of the video system and the compression stages. The result will be a quantum leap in the quality and features of digital video surveillance systems.
When most of us think of digital video compression techniques, we think of the CODECs standardized by the Motion Pictures Experts Group (MPEG). These include MPEG2 of DVD and digital TV fame, as well as MPEG4 part10 (H.264), generally considered to be the natural successor to the aging MPEG2 standard. These CODECs, rather than being rigid in their application, are best thought of as a tool bag of possible techniques that can be applied to a video stream to perform the desired compression. Which tools are used and how they are applied can significantly affect the quality and size of the compressed video stream.
In video surveillance applications, the type of video "footage" captured is generally very different from that captured for television or for movies. As a result, the tool selection made by a surveillance encoder can be very different from a broadcast encoder. A surveillance camera might, for example, be monitoring a hallway in an office building. In this case, the hallway might be deserted from six in the evening until eight the following morning, and be similarly quiet during the weekend. The encoder, therefore, can use different criteria to select appropriate tools for the compression. Tools and techniques that would be infeasible for other video applications might yield perfectly acceptable results for the quiet scene observed 80 percent of the time. Enter the Intelligent Encoder.
The Intelligent Encoder
The Intelligent Encoder consists of tightly coupled analytics and compression engines. The analytics engine is used to examine the scene and determine if any pre-selected criteria are met. Criteria might include the presence of motion, the absence of motion, sudden changes in light level or rapid scene changes. The results of the analysis are used to configure the encoder engine for optimum quality and compression levels based on the dynamics of the scene. The ability to radically change encoder parameters based on the scene dynamics results in higher average compression ratios. This lowers bit rates and makes more efficient use of storage or transmission bandwidth. Figure 1 shows a block diagram of a typical intelligent encoder.
Figure 1: Block Diagram of an Intelligent Encoder
The maximum efficiency of an Intelligent Encoder is obtained by bounding encode parameters in terms of quality, bit rate, resolution, or frame rate, and defining a time period over which the defined bounds are to be applied. In this way, the encoder itself is able to optimize the consumption of the "bit budget" based on the scene dynamics and the level of interest that the observer is likely to have in the encoded stream.
Next: Setting bounds on the encode parameters, Constant Quality bit rates
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