microprocessor, memory interfaces and stereo matching algorithm circuit module. The stereo matching algorithm core is modeled by the Matlab-based DSP Builder. The system can process many different sizes of stereo pair images through a configuration interface. The maximum horizon resolution of stereo images

We exploit the correlations between 3D-stereoscopic left-right image pairs to achieve high compression factors for image frame storage and image stream transmission. In particular, in image stream transmission, we can find extremely high correlations between left-right frames offset in time

parameter, its maximization results in a closed form solution, resulting in reduced complexity for its use in matching techniques. Application of the proposed measure in a number of benchmark stereo pair images reveals its superiority over existing correlation-based techniques used for sub-pixel accuracy. 1

Human stereo vision works by fusing a pair of perspective images with a purely horizontal parallax. Recent developments suggest that very few varieties of multiperspective stereo pairs exist. In this paper, we introduce a new stereo model, which we call epsilon stereo pairs, for fusing a broader

between pairs of frames and linked into image trajectories at video rate. Robust estimates of the camera motion are then produced from the feature tracks using a geometric hypothesize-and-test architecture. This generates what we call visual odometry, i.e. motion estimates from visual input alone

We exploit the correlations between 3D-stereoscopic left-right image pairs to achieve high compression factors for image frame storage and image stream transmission. In particular, in image stream transmission, we can find extremely high correlations between left-right frames offset in time

In this paper we analyze in some detail the geometry of a pair of cameras, i.e. a stereo rig. Contrarily to what has been done in the past and is still done currently, for example in stereo or motion analysis, we do not assume that the intrinsic parameters of the cameras are known (coordinates

from motion under the assumption that the environment is static. Along with the image sequence, it tracks feature points to get corresponding points for stereo matching. Using stereo pair images taken at selected observation points, the method estimates the relative relations of camera positions

of elevation features microwave optical etc. The stereo pair images have a great potentiality in the study of terrain analysis. The present study deals with the generation of Digital Elevation Model (DEM) using CARTOSAT-1 stereo data and retrieval of terrain attributes thereof for western Dehradun area

This paper describes a new algorithm for solving the N-camera stereo correspondence problem by transforming it into a maximum-flow problem. Once solved, the minimum-cut associated to the maximumflow yields a disparity surface for the whole image at once. This global approach to stereo analysis