The Kinetic Depth Effect and Identification of Shape
Abstract
This paper introduces an objective shape-identification task for measuring the kinetic depth effect. The observer views an array of many randomly positioned dots that move from frame to frame. The dot motions define a 3D shape consisting of bumps and depressions on an otherwise flat ground. On each trial, a presented shape is chosen from a large lexicon of shapes that vary in size, position, and number of bumps. The observer's task is to identify the shape and its overall direction of rotation. Identification accuracy in the 3D shape identification task is an objective measure, with a low guessing base rate, of the observer's perceptual ability to reconstruct a global 2D motion flow field. Objective accuracy data are shown to be generally consistent with previously obtained subjective rating judgments of depth and coherence. Along with motion cues, rotation of real 3D dot-defined shapes inevitably produces a cue of changing dot density. By using a dot-lifetime manipulation, to control dot density in our computer generated shapes, we show that changing density is neither necessary nor sufficient to account for observer's performance; i.e., motion is sufficient for the KDE. Extraction of motion cues from 6 optimally relevant locations would support perfect KDE performance with our stimuli. A simplified 2D motion identification task with 6 perceptually flat flow-fields was derived from the 3D KDE task. Subjects' performance in the 2D and 3D tasks is equivalent, indicating that the information processing capacity in KDE is comparable to information processing in other domains. Visual perception.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1987
- Accession Number
- ADA211481
Entities
People
- Barbara A. Dosher
- George Sperling
- Mark E. Perkins
- Michael S. Landy
Organizations
- New York University