Pedestrian Detection - An important part of Video Analytics
Pedestrian Detection using cameras with advanced features like Embedded Video Analytics can assist in managing crowds at a big event, or even managing foot traffic and access to an office or building in terms of security. Due to the rise in crime in public spaces like train stations, shopping malls, near ATMs and in hospitals, the need to detect and gather data on pedestrians has become more crucial. Many cities nowadays have massive CCTV networks with this type of software to observe what is happening on the streets by detecting and counting people.
In traditional pedestrian detection methods counting was done manually through an observer, for automatic video surveillance variants of DL algorithms are used. The most challenging task for automatic video surveillance is to detect and track the suspicious pedestrian activity. When a crime is committed this footage can be used as evidence and a conviction can follow due to solid evidence being available.
The main biometric features used for personal identification in visual surveillance systems are the human face and gait. Additional features include facial recognition, speech recognition and behaviour analysis. This breaks down a multitude of barriers in terms of crime solving as there is enough information to not only catch the activity on camera but also obtain more details about the activity like what was said in an interaction.
In your building you can monitor if someone has entered, who that person was, who they spoke to and what they said, with a good system. In terms of securing your work space, hospital, hotel or shopping mall the possibilities are endless.
The three stages of pedestrian detection are video acquisition, human detection and its tracking. As people are complex moving objects, detecting them and deriving information from that is a very difficult task. One has to take all the environmental noise into account, for example backgrounds with different colours, other moving objects and people in them. The quality of the camera and its position is important. The camera has to deal with varying light like stages of day and night, and changes in speed of movement also present challenges. Shadows or the person moving out of sight of the camera’s view further complicate the detection and tracking process.
The technology we have today has evolved to surpass these challenges and there has been much success with current Pedestrian Detection Embedded Video Analytics, and it is widely used.
A highly effective system uses a combination of types of cameras, for example fixed and static lens cameras, all of which we have in the Impulse Embedded Video Analytics suite of cameras.
Impulse brings you world-class Industrial Grade Video Surveillance and Networking Systems, which include cameras with advanced features like Embedded Video Analytics with Pedestrian Detection. This feature is part of the Embedded Video Analytics suite in Impulse CCTV cameras.