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Computational Video

A.C.E. Surveillance (Annotated Critical Evidence)

A.C.E. surveillance is a new word in the security industry. It is based on the advanced video-recognition technology that enables a new generation of video surveillance systems that are capable of automatically generating and managing the information about specific objects and actions captured in video.

The project started in 2005 in response to the needs from security industry, and is ongoing. It will address several problems with current video surveillance systems.

Problems from the end-user standpoint:

Recording space problem: This deals with the excessive amount of video data which usually saved somewhere for be analyzed when needed. This is the way presently commercially available DVRs (Digital Video Recorders) work. -- They digitize 24 (or 48 or more) hours of video on hard-drive, which can then be viewed and analyzed by a human when needed. The need to review the recorded surveillance data usually arises post-factum - after a criminal act has been committed.
Data management problem: This problem is not only about not having a big hard-drive, but also a problem of not having time to go though all recorded data searching for what you need. Having too much stored data is just as bad as not having any data at all, since, if the amount of data is so large that it cannot be managed within reasonable amount of time and efforts, it is useless. Therefore, it is critical for the video surveillance to be operational to store only that video data which is useful, i.e. the data containing new evidence.

Problems from the video recognition research standpoint:

Video quality: low resolution, blurring, out-of-focus, interlacing, due to wireless technology limitations
Complexity and diversity of scenarios and tasks that have to be executed and integrated.

Performance criteria for the A.C.E surveillance system:

To resolve the data management and recording space problems, the surveillance system has to satisfy the following criteria. It should:

provide data, such as evidence, that would be both useful and easily managed
be affordable, easily installed and operated - i.e. run on a desktop computer with off-the-shelf cameras: web-cams, CCTV cameras or hand-held, which can be possibly wireless for viewing remote areas
run in real-time, 24/7, non-stop everyday, and, at the same time
be merciful to hard-drive space and processing time – be as automated as possible

Current video surveillance technology does not meet these criteria. What has been developed as a result of our research is a new type of the video surveillance technology that does.

A demo of this technology that runs with an arbitrary USB camera is available for testing for download.

Research Contact

Dr. Dmitry Gorodnichy
Research Officer
Computational Video
NRC Institute for Information Technology
1200 Montreal Road
Building M-50, Room C-330
Ottawa, ON K1A 0R6
Telephone: +1 (613) 998-5298
Fax: +1 (613) 952-0215
E-mail: Dmitry Gorodnichy

Business Contact

Dr. George Forester
Group Coordinator, Business Development
Business Development Office
NRC Institute for Information Technology
1200 Montreal Road
Building M-50, Room 203
Ottawa, ON K1A 0R6
Telephone: +1 (613) 993-3478
Fax: +1 (613) 952-0074
E-mail: George.Forester@nrc-cnrc.gc.ca