Dallmeier integrates VCA technology into its serial cameras 5000

Video Content Analysis technology enables detection and classification of all potentially relevant events. Metadata is stored in a database in the recording system, being the storage space required for non-relevant events negligible.

In the Age of Artificial Intelligence, IP cameras are no longer just devices that generate images but have been covered in intelligent solutions that are part of a video surveillance infrastructure. Dallmeier follow these developments by integrating VCA technology (Video Content Analysis – video analysis) in its range of serial cameras 5000 to enable intelligent incident search in video stream recordings.

Video Content Analysis technology enables automated analysis of observational situations that uses video data to detect and classify relevant objects and incidents, as well as offering an intelligent filter function to manage large volumes of recorded material.

The filtering of the observation situation carried out by the camera, with the help of preset classifications, enables real-time video analysis, so that incorrectly detected incidents can be minimized in advance and are not even taken into account when storing them. For its part, relevant incidents can be stored on the server along with associated metadata.

this functionality prevents the user from having to waste time looking at large volumes of archived material, but you can find the incidents of interest more selectively and efficiently with the help of stored metadata. Valuable time is saved and suspicious instances can be verified quickly and easily.

Unlike motion detection (simple detection of movement), that performs the analysis on device only after the events have occurred, VCA technology performs the analysis in advance and in real time, and classifies the objects it detects.a the results of the analysis are continuously transmitted to the recording system, along with the corresponding metadata, as an incident report.

With VCA technology, five different analysis classifications can be assigned depending on the field of application: intrusion detection, line crossing detection (line-crossing), object classification, face detection and sabotage.

In addition to the basic data, as the date, time and location of incidents, additional filters can be used so that a wide spectrum of information can be stored, such as the object class or duration of the incident. This can contribute to a search and evaluation, precisely and distinguish between classes of objects and filter them (such as vehicles or people).

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