Key considerations when selecting a video compression algorithm: Part 2

A comparison between H.264, MJPEG and other common compression schemes for surveillance video


Frame-based compression like MJPEG suffers no video quality degradation with fast moving objects. If you are using temporal compression like H.264 to capture fast objects, then choose your H.264 profile wisely because all H.264 profiles are not created equal. There is a direct relationship between the video quality of moving objects and the H.264 profile chosen. Lower quality H.264 cameras use a very "light" profile like the one known as "Constrained Baseline", and this can result in substantially lower video quality for moving objects. As with many technologies, there is no free lunch; less computing power in the camera equals lower performance.

To illustrate, consider a camera with a 20-foot field of view. A normal person running past that camera would be in the field of view for about 2 seconds (100-meter world record holder Usain Bolt could cross the camera's field of view in 0.6 seconds!). A low quality H.264 camera running at 7.5 frames/second (fps) may not capture a single true image (key frame) of that normal person, instead producing 15 "estimated" frames, thus making clear video of the subject improbable. For this reason, we recommend considering H.264 only when you need 15 fps video or higher. For those applications where the surveillance system needs to capture even faster objects such as moving cars or fast moving people, the frame rate should be even higher if the video system is to do its job appropriately. Of course, these higher frame rates will increase the bandwidth and storage requirements of the overall system.

7. Camera Motion [Video Environment]

Camera Motion represents the worst case scenario for temporal compression algorithms because it represents 100 percent scene motion at all times (see Consideration #5). Camera motion can be caused by wind or vibrations, a pole swaying, or by panning, tilting, or zooming (PTZ) a camera. It can also be the result of a mobile application such as cameras mounted in trains, buses, police cars or emergency vehicles. H.264 video from an actively panning PTZ camera is very poor quality, which underscores the critical role scene motion plays in the selection of H.264 compression for a given application. For this reason, we recommend a frame-based compression like MJPEG for any mobile application or PTZ camera application, regardless of the impact of the other considerations we have outlined above.

In closing, here are some important rules of thumb based on the considerations outlined above:

  • When using H.264 compression, be sure to factor in weather and lighting conditions when calculating bandwidth and storage needs.
  • Select H.264 when there will be less than 20 percent maximum motion in the scene.
  • Select MJPEG or utilize high frame rate H.264 compression when attempting to capture faster moving objects.
  • Select MJPEG if the camera is on a mobile platform or in a PTZ unit.

In the third and final article of this series, look for a discussion of our final two considerations - the user requirements for recording and live viewing -- as well as more recommendations based on all nine considerations for what compression methodology is best for your application.
 

About the authors:

Pete DeAngelis of IQinVisionPeter DeAngelis is president and chief executive officer megapixel surveillance camera manufacturer for IQinVision.  Before joining IQinVision, Peter was co-founder, Vice President of Engineering, and Chief Technical Officer of San Diego-based Rokenbok Toy Company. Previously, he served as Director of New Products at Newpoint Corporation, a division of Proxima Corporation. Mr. DeAngelis’ successful career in start-up organizations began with PC Devices Inc., a company he founded in the early 1990s to market and sell PC-based audio products. He received a Bachelor of Science in Electrical Engineering from the University of Maine and holds numerous US and foreign patents.

Paul Bodell of IQinVisionPaul Bodell is chief marketing officer for IQinVision. He has spent over 15 years in the security industry with senior management positions at Sensor/HID, Silent Knight, and Philips CCTV. Paul is a regular contributor to top industry magazines and is active in SIA, the IP UserGroup, and other industry groups. He holds undergraduate degrees in Engineering from the University of Connecticut, Mathematics from Fairfield University, and an MBA from University of New Haven.