1. A method of video analysis, comprising: receiving plural video streams, each video steam providing a series of video images of a monitored location; detecting a human object within the video images; determining a three dimensional (3D) hull corresponding to the human object within the video images; determining initial pose hypotheses of the human object within the video images, the initial pose hypotheses comprising a plurality of pose predictions each associated with a first probability value; mapping a plurality of simple geometric volumes to each of the pose predictions of the initial pose hypotheses to obtain a plurality of corresponding coarse 3D human models; comparing each of the corresponding coarse 3D human models to the 3D hull; in response to the comparing of each of the corresponding coarse 3D human models to the 3D hull, modifying pose predictions of the initial pose hypotheses to obtain refined pose hypotheses; for each of the pose predictions of the refined pose hypotheses, mapping at least one standard human model to a coarse 3D human model associated with the pose prediction to obtained an associated refined 3D human model; comparing each of the refined 3D human models to at least one of the video images to select an optimum 3D human model as representing the human object detected within the video images; and based on the selected optimum 3D human model, automatically detecting at least one of an event represented within at least one of the video images, a characteristic of the human object and a second object within at least one of the video images.