Scene invariant multi camera crowd counting
We propose a crowd counting algorithm that is scene invariant and operates across multiple cameras. Camera calibration is used to normalise features between views and to achieve scene invariance. The algorithm compensates for regions of overlap in a multi camera environment using calibration. An investigation into the suitability of various feature types for scene invariance is conducted. A mean relative error <10% is seen on Views 13 of the PETS 2009 dataset, when trained on another scene.
scene invariant multi camera crowd counting