Andrew E. Fitzhugh

The method of constant stimuli is inefficient.

Simpson (1988) has argued that the method of constant stimuli is as efficient as adaptive methods of threshold estimation, and has supported this claim with simulations. We show that Simpson’s simulations are not a reasonable model of the experimental process, and that more plausible simulations confirm that adaptive methods are much more efficient than the method of constant stimu1i.

Practical Methods for Geometric and Photometric Correction of Tiled Projector

We describe a novel, practical method to create largescale, immersive displays by tiling multiple projectors on curved screens. Calibration is performed automatically with imagery from a single uncalibrated camera, without requiring knowledge of the 3D screen shape. Composition of 2D-mesh-based coordinate mappings, from screen-tocamera and from camera-to-projectors, allows image distortions imposed by the screen curvature and camera and projector lenses to be geometrically corrected together in a single non-parametric framework. For screens that are developable surfaces, we show that the screen-to-camera mapping can be determined without some of the complication of prior methods, resulting in a display on which imagery is undistorted, as if physically attached like wallpaper. We also develop a method of photometric calibration that unifies the geometric blending, brightness scaling, and black level offset maps of prior approaches. The functional form of the geometric blending is novel in itself. The resulting method is more tolerant of geometric correction imprecision, so that visual artifacts are significantly reduced at projector edges and overlap regions. Our efficient GPUbased implementation enables a single PC to render multiple high-resolution video streams simultaneously at frame rate to arbitrary screen locations, leaving the CPU largely free to do video decompression and other processing.

Discriminability metric based on human contrast sensitivity.

We evaluated a metric for predicting the discriminability of different digitized versions of alphanumeric characters. The metric is based on the assumption that there exists a visual filter such that discriminability is monotonic with the contrast energy in the visually filtered difference between stimuli. To test this hypothesis, we presented two same or different digital versions of a master character and asked subjects to indicate whether the characters were the same or different in a forced-choice procedure with feedback. The filtered contrast energy difference was calculated by convolving the difference between stimulus pairs with filters derived from published human contrast sensitivity functions, following an initial nonlinear transformation of stimulus intensity, and summing the squared result. For some types of stimulus difference, such as contrast quantization errors and Gaussian blurring, performance on discrimination tasks is monotonically related to the contrast energy of the filtered difference vector. The results are consistent with the hypothesis that there exists a single psychometric function that can predict the discriminability of different digitized versions of characters when displayed on various devices.