Mobility and low contrast trip hazard avoidance using augmented depth

Abstract

OBJECTIVE: We evaluated a novel visual representation for current and near-term prosthetic vision. Augmented depth emphasizes ground obstacles and floor-wall boundaries in a depth-based visual representation. This is achieved by artificially increasing contrast between obstacles and the ground surface via a novel ground plane extraction algorithm specifically designed to preserve low-contrast ground-surface boundaries. APPROACH: The effectiveness of augmented depth was examined in human mobility trials compared against standard intensity-based (Intensity), depth-based (Depth) and random (Random) visual representations. Eight participants with normal vision used simulated prosthetic vision with 20 phosphenes and eight perceivable brightness levels to traverse a course with randomly placed small and low-contrast obstacles on the ground. MAIN RESULTS: The number of collisions was significantly reduced using augmented depth, compared with intensity, depth and random representations (48%, 44% and 72% less collisions, respectively). SIGNIFICANCE: These results indicate that augmented depth may enable safe mobility in the presence of low-contrast obstacles with current and near-term implants. This is the first demonstration that an augmentation of the scene ensuring key objects are visible may provide better outcomes for prosthetic vision.