A PERTURBATION ANALYSIS OF DEPTH-PERCEPTION FROM COMBINATIONS OF TEXTURE AND MOTION CUES

We examined how depth information from two different cue types (object motion and texture gradient) is integrated into a single estimate in human vision. Two critical assumptions of a recent model of depth cue combination (termed modified weak fusion) were tested. The first assum ption is that the overall depth estimate is a weighted linear combinat ion of the estimates derived from the individual cues, after initial p rocessing needed to bring them to a common format. The second assumpti on is that the weight assigned to a cue reflects the apparent reliabil ity of that cue in a particular scene. By this account, the depth comb ination rule is linear and dynamic, changing in a predictable fashion in response to the particular scene and viewing conditions. A novel pr ocedure was used to measure the weights assigned to the texture and mo tion cues across experimental conditions. This procedure uses a type o f perturbation analysis. The results are consistent with the weighted linear combination rule. In addition, when either cue is corrupted by added noise, the weighted linear combination rule shifts in favor of t he uncontaminated cue.