Human heading judgments in the presence of moving objects

Abstract

When moving toward a stationary scene, people judge their heading quite well from visual information alone. Much experimental and modeling work has been presented to analyze how people judge their heading for stationary scenes. However, in everyday life, we often move through scenes that contain moving objects. Most models have difficulty computing heading when moving objects are in the scene, and few studies have examined how well humans perform in the presence of moving objects. In this study, we tested how well people judge their heading in the presence of moving objects. We found that people perform remarkably well under a variety of conditions. The only condition that affects an observer's ability to judge heading accurately consists of a large moving object crossing the observer's path. In this case, the presence of the object causes a small bias in the heading judgments. For objects moving horizontally with respect to the observer, this bias is in the object's direction of motion. These results present a challenge for computational models.The task ofnavigating through a complex environment requires the visual system to solve a variety of problems related to three-dimensional (3-D) observer motion and object motion. To reach a desired destination, people must accurately judge their direction of motion. To avoid hitting objects in the scene, they must be able to judge the position of stationary objects and the position and 3-D motion of objects moving relative to themselves. Because we often move through scenes that contain moving objects, our heading judgments ideally should not be affected by the presence of these objects. For example, a driver on a busy street must make accurate headingjudgments in the presence of other moving cars and pedestrians. It is clear from psychophysical experiments that, for translational motion, people can accurately judge their heading when approaching stationary scenes (Crowell & Banks, 1993;Crowell, Royden, Banks, Swenson, & Sekuler, 1990;Rieger & Toet, 1985;van den Berg, 1992;Warren & Hannon, 1988, 1990. However, little has been done to measure human ability to judge heading in the presence of moving objects. Furthermore, most computational models have been designed to make heading judgments given stationary scenes. The presence ofmoving objects in the scene adversely affects their performance. In this paper, we present experiments that test whether the presence of moving objects similarly affects human ability to judge heading. To illustrate the difficulties involved in judging heading in the presence of moving objects, we first describe some of the computational models that have been put forth to compute heading from visual input. Most of these models have been developed to solve the problem of computing both the translation and the rotation components of motion for an observer moving through a stationary scene. We will focus our discussion on models that are the most biologically plausible. Following the discussion of computational modeling, we briefly summarize previou...

A neural model of visually guided steering, obstacle avoidance, and route selection.

“…Although early studies of heading perception assumed a static environment, real world navigational situations usually involve the traversal of environments containing stationary and moving objects. The presence of independently moving objects in the optic flow field has been shown to impair heading judgment only when the object moves across the direction of travel, obscuring the veridical focus of expansion (Warren & Saunders, 1995;Royden & Hildreth, 1996). Subjects can also tolerate significant amounts of velocity noise in the optic flow display, suggesting that heading perception primarily relies on the directional pattern of motion in the optic flow field (Warren, Blackwell, Kurtz, Hatsopoulos, & Kalish, 1991).…”

A neural model of how the brain computes heading from optic flow in realistic scenes

“…Differential motion models offer the best explanation of human data showing misperceptions of heading in the presence of large moving objects (Royden & Hildreth, 1996, Royden, 2002Warren, 1998). Moving objects only significantly affect heading perception when they cover a large part of the visual field, and they affect heading differently depending on their direction of motion.…”

“…Differential motion models (Rieger & Lawton, 1985;Hildreth, 1992;Royden, 1997Royden, , 2002Royden & Hildreth, 1996) and decomposition models (Heeger & Jepson, 1992;Lappe & Rauschecker, 1994 take great pains to remove eye rotations from retinal flow before estimating heading. However, as also noted in the Introduction, humans are affected by rotations in the optic flow field if they are not due to a real eye movement.…”

“…Most models show heading accuracy within 1-2 degrees, matching human data, and tend to be robust to noise in retinal flow. Differential motion models (Hildreth, 1992;Rieger & Lawton, 1985;Royden, 1997Royden, , 2002Royden & Hildreth, 1996) and decomposition models (Heeger & Jepson, 1992;Lappe & Rauschecker, 1993 remove eye rotations from retinal flow before estimating heading.…”

How Optic Flow and Inertial Cues Improve Motion Perception

“…However, object motion is known to induce biases and reduce the accuracy of heading perception in the visual system (Warren and Saunders 1995;Saunders and Warren 1996). The movement of objects through space disrupts the pattern of optic flow due to the motion of the observer, making it difficult to distinguish between self-motion and object motion (Warren and Saunders 1995;Royden and Hildreth 1996).…”