Intelligent Network Video: Understanding Modern Video by Fredrik Nilsson

By Fredrik Nilsson

Carrying on with within the culture of the bestselling first variation, this booklet examines networked surveillance video recommendations. It offers the most recent info on undefined, software program, and networking services of the newest cameras and DVRs. It addresses in complete element up-to-date requisites on MPEG-4 and different electronic video codecs, solution merits of analog v. electronic, clever video services, body fee keep an eye on, and indoor/outdoor installations components. New chapters comprise cloud computing, criteria, and thermal cameras.

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It may also be nonsemantic, in which case it is a question of extracting numerical descriptors that encode the appearance of the objects present in the scene so as to find other observations of those objects at other times in the same video or in other videos, typically for the purposes of information gathering. 2. On-line generic indexing Currently, indexing of videos is done by a posteriori processing of the recorded streams, which requires large computational capacities. However, it is envisageable that in the future, systems will emerge, which offers constant generic indexing, for which certain metadata will be extracted in parallel with the acquisition of the video stream, and stored alongside it.

Focus on Railway Transport 23 compensating for the difficulties encountered by the image interpretation methods. A bus was equipped with numerous cameras and microphones, and a sound and image database was created by filming scripted scenes. Up until that point, no such database had been available. It enabled testers to show the problems and the scientific hurdles standing in the way of the deployment of image/sound processing/analysis in the context of mobility. On the one hand, the project focused on motion analysis algorithms, and in particular on background/pattern segmentation methods that help detect the different entities on the bus, such as passengers or objects that they are carrying.

In EVAS, two techniques were used: generative modeling by a mixture of Gaussians and discriminative modeling by support vector machines [BER 07]. 2. Applications to railway transport Very soon, surveillance systems came to be installed aboard other public transport vehicles such as trains and metros. Developing automatic systems to interpret images and sounds and conceiving high-throughput communication systems between the onboard environment and the infrastructure on the ground have become two important axes for research in the field of railways.

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