Vergence Micromovements and Depth Perception

A new approach in stereo vision is proposed in which 3D depth information is recovered using continuous vergence angle control with simultaneous local correspondence response. This technique relates elements with the same relative position in the left and right images for a continuous sequence of vergence angles. The approach considers the extremely fine vergence movements (micromovements) about a given fixation point within the depth of field boundaries. It allows the recovery of 3D depth information given the knowledge of the geometry of the system and a sequence of pairs [oi,Ci], where a, is the i vergence angle and C, is the i matrix of correspondence responses. Due to its local operation characteristics, the resulting algorithms are implemented in a modular hardware scheme using transputers. Unlike currently used algorithms, there is no need to compute depth from disparity values; at the cost of the acquisition of a sequence of images during the micromovements. Experimental results from physiology and psychophysics suggest that the approach is biologically plausible. Therefore, the approach proposes a functional correlation between the vergence micromovements, depth perception, stereo acuity and stereo fusion. The perception of the 3D-distance, depth, of objects using stereo images have been studied by many researchers for a long time. Some of these studies use vergence camera systems [1] integrating position control, image acquisition and depth processing on the modality of vision system named "active vision" [2]. Following this line of research, the present work analyses the correlation between the real time depth acquisition and the extremely fine vergence movements (micromovements) of the cameras about the fixation point. We assume that these movements are synchronized between the two cameras. The continuous vergence micromovements differ from the vergence, translation and rotation movements used on the other methods to fixate the cameras on a new fixation point. The previous methods (using particular techniques as multi-resolution) compute some depth-map or depth directly from the acquisition of the left and right images at this fixation point, i.e., using two images and some stored information (estimation) about the depth-map they are able to infer the current depth at the correctly matched image points. Generally, * Researcher at the National Institute of Space Research (INPE), Sao Jose dos Campos, Sao Paulo, Brazil. The support from the Swedish National Board for Industrial and Technical Development, NUTEK, is gratefully acknowledged. I would like to thank Prof. Ruzena Bajcsy and Prof. Jan-Olof Eklundh for the support to the development of this work as well as Kourosh Pahlavan, Akihiro Horii and Thomas Uhlin for valuable help when using the KTH head-eye system. BMVC 1992 doi:10.5244/C.6.38