**corners.**The corner detector implemented here is our own version of the Plessey algorithm developed by Harris and Stevens. This involves the generation of a corner strenth image, followed by maxima detection and peak fitting to obtain the corner locations to sub-pixel accuracy. Although detected corners do not always correspond to intersection vertices identified by edge fitting they still provide accurate positional information at reproduceable positions in the image from three dimensional objects. Other corner processors may give locations which are more consistent with edge detection processes.sigma : The parameter of the Gaussian convolution profile used to filter the image prior to corner detection. This effectively sets the minimum scale of detected features. precision : The ratio of the smallest stored value of the Gaussian convolution profile.

**rectify.**Use the current stereo camera geometry to compute the rectified locations of each corner. This process must be performed prior to stereo matching and geometry recovery. Rectified locations are added as extra data to the existing structure so that the original location of each corner is preserved. There is thus no need for the equivalent derectification process in the*Edge Tool*.**stereo.**A correlation based matching algorithm that matches corner features which are consitent with the current parallel camera geometry. As this method is correlation based there is a fundamental requirement that the local image patch surrounding each corner is similar. Thus corners on extremal boundaries will normally not be sucessfully matched.Stereo Parameters: lowdisp : The lower limit of the allowed disparity range in fractions of image width from the centre of each region of interest. updisp : The upper limit of the disparity range. width : The epi-polar band width used to define the valid matching area (set large for poor camera geometry). correlation : The minimum cross correlation measure required between corners for them to be regarded as candidate matches. uniqueness : The minimum difference in correlation values between candidate matches before a match is labelled ambiguous. This parameter is particularly important in regions of many similar features where the likelihood of getting a missmatch is high.

**temporal.**As corner features are well located in both directions on the image plane they can be matched between temporal frames with relatively weak assumptions about the relative transformations between images.Temporal Parameters: height : Maximum vertical shift allowed between successive locations of a corner in the image plane relative to the centre of the region of interest. width : Maximum horizontal shift.

**geom.**Compute the 3D location of uniquely matched stereo corners and make them available for display in the*threed Tv*.