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 reliable and accurate instantaneous flow estimates. The integration employs robust 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 readily combined with parameterized flow and acceleration models. A demonstration of performance on image sequences of typical human actions taken with a high frame-rate camera, is given. 1 Introduction Image motion estimation involves relating spatial and temporal changes in image intensity to estimates of image flow. Articulated and deformable motions such as those encountered in images of humans in motion give rise to image sequences having, instantaneously, a wide range..