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Active gaze control improves optic flow-based segmentation and steering.

Raudies F, Mingolla E, Neumann H - PLoS ONE (2012)

Bottom Line: To support our suggestion we derive an analytical model that shows: Tangentially fixating the outer surface of an obstacle leads to strong flow discontinuities that can be used for flow-based segmentation.Fixation of the target center while gaze and heading are locked without head-, body-, or eye-rotations gives rise to a symmetric expansion flow with its center at the point being approached, which facilitates steering toward a target.We conclude that gaze control incorporates ecological constraints to improve the robustness of steering and collision avoidance by actively generating flows appropriate to solve the task.

View Article: PubMed Central - PubMed

Affiliation: Center of Excellence for Learning in Education, Science, and Technology, Boston University, Boston, Massachusetts, United States of America. fraudies@bu.edu

ABSTRACT
An observer traversing an environment actively relocates gaze to fixate objects. Evidence suggests that gaze is frequently directed toward the center of an object considered as target but more likely toward the edges of an object that appears as an obstacle. We suggest that this difference in gaze might be motivated by specific patterns of optic flow that are generated by either fixating the center or edge of an object. To support our suggestion we derive an analytical model that shows: Tangentially fixating the outer surface of an obstacle leads to strong flow discontinuities that can be used for flow-based segmentation. Fixation of the target center while gaze and heading are locked without head-, body-, or eye-rotations gives rise to a symmetric expansion flow with its center at the point being approached, which facilitates steering toward a target. We conclude that gaze control incorporates ecological constraints to improve the robustness of steering and collision avoidance by actively generating flows appropriate to solve the task.

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Summary of the local flow derivative analysis.a) Approaching a target while fixating the surface nx ≠ 0, ny = 0, and nz≠0 yields divergence and Type I shear components if moving sideward; curl and Type II shear components if moving up/downward; a divergence component if moving forward, compare with the Table 1. For the case nx = 0, ny ≠ 0, and nz ≠ 0 the same components occur if swapping x and y, compare with the Table 2. b) Avoiding an obstacle by tangentially fixating its edge surface yields the same flow derivative components as in a) for the case nx = 1, ny = 0, and nz = 0. c) Fixation of an apical edge yields all four components if moving along the optical axis. Sideward movement results in divergence and Type I shear and up−/downward movement in curl and Type II shear components.
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pone-0038446-g003: Summary of the local flow derivative analysis.a) Approaching a target while fixating the surface nx ≠ 0, ny = 0, and nz≠0 yields divergence and Type I shear components if moving sideward; curl and Type II shear components if moving up/downward; a divergence component if moving forward, compare with the Table 1. For the case nx = 0, ny ≠ 0, and nz ≠ 0 the same components occur if swapping x and y, compare with the Table 2. b) Avoiding an obstacle by tangentially fixating its edge surface yields the same flow derivative components as in a) for the case nx = 1, ny = 0, and nz = 0. c) Fixation of an apical edge yields all four components if moving along the optical axis. Sideward movement results in divergence and Type I shear and up−/downward movement in curl and Type II shear components.

Mentions: Our work analyzes flow derivatives that occur for different forms of self-motion and gaze direction. Figure 3 provides an outline and overview of this idea. On the left-hand side of the figure three scenarios are displayed: fixation at the center of a target object, fixation parallel to the edge of an obstacle, and fixation at the outer edge of an obstacle called an apical edge. The first column shows drawings of these 3D scenarios of facing a plane, looking tangential to a plane, and looking at an outer edge that has the background on the right side, in this example. The last column of Figure 3 shows the different flow derivative components of divergence, curl, and shear that occur in these configurations. These derivative components are characterized by the normal vector of the surface with components nx, ny, and nz, and the translational self-motion vector with components vx, vy, and vz. Note that flow derivatives are encoded using the same icons as in Figure 2. According to our derived analytical model some types of derivatives only occur for a specific configuration. For instance, in the target approach in Figure 3a with nx≠0, ny = 0, and nz≠0 and if the observer translates only along the x-axis, only divergence and Type I shear occur. See Figure 3a the table in the first row and there the entries for vx. More details about the analytical model and its comparison to responses from a biologically motivated flow derivative detector are given next.


Active gaze control improves optic flow-based segmentation and steering.

Raudies F, Mingolla E, Neumann H - PLoS ONE (2012)

Summary of the local flow derivative analysis.a) Approaching a target while fixating the surface nx ≠ 0, ny = 0, and nz≠0 yields divergence and Type I shear components if moving sideward; curl and Type II shear components if moving up/downward; a divergence component if moving forward, compare with the Table 1. For the case nx = 0, ny ≠ 0, and nz ≠ 0 the same components occur if swapping x and y, compare with the Table 2. b) Avoiding an obstacle by tangentially fixating its edge surface yields the same flow derivative components as in a) for the case nx = 1, ny = 0, and nz = 0. c) Fixation of an apical edge yields all four components if moving along the optical axis. Sideward movement results in divergence and Type I shear and up−/downward movement in curl and Type II shear components.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3375264&req=5

pone-0038446-g003: Summary of the local flow derivative analysis.a) Approaching a target while fixating the surface nx ≠ 0, ny = 0, and nz≠0 yields divergence and Type I shear components if moving sideward; curl and Type II shear components if moving up/downward; a divergence component if moving forward, compare with the Table 1. For the case nx = 0, ny ≠ 0, and nz ≠ 0 the same components occur if swapping x and y, compare with the Table 2. b) Avoiding an obstacle by tangentially fixating its edge surface yields the same flow derivative components as in a) for the case nx = 1, ny = 0, and nz = 0. c) Fixation of an apical edge yields all four components if moving along the optical axis. Sideward movement results in divergence and Type I shear and up−/downward movement in curl and Type II shear components.
Mentions: Our work analyzes flow derivatives that occur for different forms of self-motion and gaze direction. Figure 3 provides an outline and overview of this idea. On the left-hand side of the figure three scenarios are displayed: fixation at the center of a target object, fixation parallel to the edge of an obstacle, and fixation at the outer edge of an obstacle called an apical edge. The first column shows drawings of these 3D scenarios of facing a plane, looking tangential to a plane, and looking at an outer edge that has the background on the right side, in this example. The last column of Figure 3 shows the different flow derivative components of divergence, curl, and shear that occur in these configurations. These derivative components are characterized by the normal vector of the surface with components nx, ny, and nz, and the translational self-motion vector with components vx, vy, and vz. Note that flow derivatives are encoded using the same icons as in Figure 2. According to our derived analytical model some types of derivatives only occur for a specific configuration. For instance, in the target approach in Figure 3a with nx≠0, ny = 0, and nz≠0 and if the observer translates only along the x-axis, only divergence and Type I shear occur. See Figure 3a the table in the first row and there the entries for vx. More details about the analytical model and its comparison to responses from a biologically motivated flow derivative detector are given next.

Bottom Line: To support our suggestion we derive an analytical model that shows: Tangentially fixating the outer surface of an obstacle leads to strong flow discontinuities that can be used for flow-based segmentation.Fixation of the target center while gaze and heading are locked without head-, body-, or eye-rotations gives rise to a symmetric expansion flow with its center at the point being approached, which facilitates steering toward a target.We conclude that gaze control incorporates ecological constraints to improve the robustness of steering and collision avoidance by actively generating flows appropriate to solve the task.

View Article: PubMed Central - PubMed

Affiliation: Center of Excellence for Learning in Education, Science, and Technology, Boston University, Boston, Massachusetts, United States of America. fraudies@bu.edu

ABSTRACT
An observer traversing an environment actively relocates gaze to fixate objects. Evidence suggests that gaze is frequently directed toward the center of an object considered as target but more likely toward the edges of an object that appears as an obstacle. We suggest that this difference in gaze might be motivated by specific patterns of optic flow that are generated by either fixating the center or edge of an object. To support our suggestion we derive an analytical model that shows: Tangentially fixating the outer surface of an obstacle leads to strong flow discontinuities that can be used for flow-based segmentation. Fixation of the target center while gaze and heading are locked without head-, body-, or eye-rotations gives rise to a symmetric expansion flow with its center at the point being approached, which facilitates steering toward a target. We conclude that gaze control incorporates ecological constraints to improve the robustness of steering and collision avoidance by actively generating flows appropriate to solve the task.

Show MeSH