Moving/Static Classification via

Moving/Static Classification via Tracking

This project deals with the problem of classifying dynamic objects out of the entire objects detected in sequential frames taken from a single moving camera and tracking them along the frames.

The challenge derives from the difficulty to seclude the dynamic objects from the static ones in a situation where all objects seem dynamic because of the motion of the camera,

In addition, the conditions of the inputs can vary a lot from each other (homogeneous background, urban background, multiplicity of dynamic objects, different speeds of camera motion, angle of filming, quality of the frames taken…) .

Algorithm modules

1.Interest point detection on the input images.

2..A creation of a graph of K-NN (K nearest neighbors ) with a constraint of maximal distance between neighbors.

3.score every edge in the graph by using the homogeneous scale assumption.

4.Groups segmentation using the graph data.