Marker based pedestrian detection using augmented reality

Pedestrian detection is a popular research topic from the last decade. Most of the pedestrian identification models are based on face recognition algorithms. It is a difficult task to detect and track individual pedestrians based on these algorithms because there is a compulsion that their faces should be towards the camera. This limitation makes face recognition algorithms inefficient to detect pedestrians from the backsides. In this paper, we proposed a method for pedestrian detection using marker recognition. Multiple pedestrians are detected and then tracked based on markers attached to their backsides. Attaching markers on backside of pedestrians helps to recognize them even when they are looking the other way. After the marker is recognized, the unique character related to that marker is displayed as a 3D object. This marker-based pedestrian detection is carried out using a mobile phone system and can be applied to embedded systems. The proposed method makes it possible to recognize up to three pedestrians located at different positions from the camera.