The phrenological mapping of the brain was one of the first attempts to correlate the mental functions of a human with specific parts of the brain and the logical, functional and executions of the limbs is to be seen as an extension of the brain.
What does this mean, the decision as to an executable function is due to logical evaluation of the current scenario, and this leads to specific actions. Again you will say what does this have to do with video analytics? The answer is short and sweet! The human sapiens and their so called superior intelligence over species, is always on the verge of concurring the new world whereby mechanical hardware receives artificial neural capabilities in making decisions on our, human, behalf. Video analytics is the brain of the "machine" and various systems and sub-systems will be deemed the spinal cord and limbs, all to achieving the set outcome.
Video Analytics or Video Content Analytics as it is used within the industry, as well is a term abused by many a manufacturer, could be misleading, especially when the term is misused as a "smart word" within the perimeter control environment.
The most important, before we can embark on this venture of explaining all about Video Analytics or Video Content Analytics, is to understand what the definition is of such. Video content analysis or Video content analytics is the ability to analyse a video image by means of set criteria. Detection or determine the results could be intelligent and the volume inside the field of view can be seen as the electronic automated equivalent of the biological visual cortex. The ability to automate effectively is used in a very wide range of industries like, maritime, safety, security, automation, home automation, transport etc. Each of these industries calls for a unique bases algorithm and even the individual tasks within the individual industries calls for a bases + task unique algorithm.
These algorithms could be installed as software on head-end and monitoring equipment or as hardware on the processing portion units. The algorithms of the Video Content Analysis allows for a huge amount of different functionalities, where Video Motion Detection and Advanced Video Motion Detection is one of the simpler forms where motion is detected within a fixed background scene. Human, Vehicle and Animal Detection and tracking are a more advanced feature and the complicated algorithm could only be done within the video analytics context. The accuracy of the system and the effectiveness of the analytics relies heavily on a good input video signal and the latter is achieved by using video enhancement technologies such as video signal denoising DSP, image stabilizing DSP, unsharpen masking techniques and even chrominance and luminance enhancing DSP units.
Another key element within the Video Analytics concept is the artificial neural networks. It is computational models, which is inspired by the central nervous systems, which allows the mechanical features to do machine learning and recognize patterns. The ability to analyze the scene accurately at high speeds, due to high frequency input values, and to adapt to the changing logarithmic values, will be the deciding factor in what system works and what is second best. Considering the above, the platform is set for a system that will be able to execute the task at hand and to accurately respond to the set criteria, with a net result of saving money for the customer. In conclusion, the different algorithms, and the associated classifiers and filters, are the determining factors.
The quality of the algorithm will be based on the correct mathematical technique for such an application. It will be impossible for the distributor or even integrator, needless to say the end-user, in which technique – or algorithm – or filter – or classifier to use for the desired application. This will lead to only one workable solution, trial and tested with the occasional shootout and proof of concept. This will be the determining factor in what system works and what not.