Temporal multi-scale models for flow and acceleration

A model for computing image flow in image sequences containing a very wide range of instantaneous flows is proposed. This model integrates the spatio- temporal image derivatives from multiple temporal scales to provide both re liable and accurate instantaneous flow estimates. The integration employs r obust regression and automatic scale weighting in a generalized brightness constancy framework. In addition to instantaneous flow estimation the model supports recovery of dense estimates of image acceleration and can be read ily combined with parameterized flow and acceleration models. A demonstrati on of performance on image sequences of typical human actions taken with a high frame-rate camera is given.