Accumulated Visual Representation for Cognitive Vision

In this paper we present a scheme for accumulating local visual information in 3D, under known motion. Information about the object’s 3D shape is provided by reconstructing local contour descriptors. This shape information is accumulated over time in three ways: 1) disambiguation: erroneous stereo correspondences that are unsuccessfully tracked are discarded. We make use of aspect cues to increase the data association selectivity. 2) correction: the full pose of the reconstructed features is corrected over time using an Kalman Filter approach. 3) completeness: multiple 2 1 2 D representations become merged, constructing a full 3D representation of the object. The described system is evaluated quantitatively on three different scenarios.