8/30/2023 0 Comments Motion parallaxUsing the estimated camera motion and the available depth map estimate, motion of the 3D points is compensated. Given a coarse, noisy and partial depth map acquired by a range-finder or obtained from a Digital Elevation Map (DFM), we first estimate the ego-motion by combining a global ego-motion constraint and a local brightness constancy constraint. We present an iterative algorithm for robustly estimating the ego-motion and refining and updating a coarse, noisy and partial depth map using a depth based parallax model and brightness derivatives extracted from an image pair. 2004 International Conference onģD, algorithm, analysis, and, based, camera, coarse, compensation, DEM, depth, digital, ego-motion, eigen-value, eigenfunctions, eigenvalues, ELEVATION, epipolar, estimation, extraction, feature, field, iteration, iterative, map, method, methods, model, model, MOTION, parallax, partial, range-finding, refinement, refining, surface However, performance was close to veridical in the CoM task-providing further evidence of mutual inconsistency between perceived stability and CoM judgments.Robust ego-motion estimation and 3D model refinement using depth based parallax model Observers underestimated stability for frustums slanting away from the edge, and overestimated stability when slanting toward it, suggesting a bias toward the center of the supporting base. Results exhibited a significant effect of all three variables on stability judgments. In the CoM task, they adjusted the height of a small ball probe to indicate perceived CoM. In the stability task, observers adjusted the horizontal position of the object relative to the precipitous edge until it was perceived to be in unstable equilibrium. Objects were slanted conical frustums that varied in their slant angle, aspect ratio, and direction of slant (pointing toward/away from the edge). Observers stereoscopically viewed a rendered scene containing a 3D object placed near a table’s edge. The current study uses a different paradigm-measuring the critical extent to which an object can "stick out" over a precipitous edge before falling off. Previously we have used the 'critical angle' of tilt to measure perceived object stability (VSS 20). Visual estimation of object stability is an ecologically important judgment that allows observers to predict objects' physical behavior. Our work proposes a new statistical platform to objectively separate changes in visual perception by quantifying the unfolding of movement, emphasizing the importance of including in the motion analyses all overt and covert aspects of motor behavior. We find that the moment-by-moment empirically estimated motor output variability can inform us of the participants’ perceptual states, detecting physiologically relevant signals from the peripheral nervous system that reveal internal mental states evoked by the bi-stable illusion. To investigate how perceptual inputs affect reach behavior, we use a depth inversion illusion (DII): the same physical stimulus produces two distinct depth percepts that are nearly orthogonal, enabling a robust comparison of competing percepts. We apply these new methods to help better understand perception-action loops. As it turns out, these movements, often overlooked as motor noise, contain valuable information that contributes to the emergence of different kinesthetic percepts. The inclusion of these motions in our analyses introduces a new paradigm in sensory-motor integration. These are largely beneath awareness, but inevitably present in all behaviors. We also quantify a new class of covert movements that spontaneously occur without instruction. How do we shift from a psychological, theorizing approach to characterize complex behaviors more objectively? We introduce a novel, objective, statistical framework, and visuomotor control paradigm to help characterize the stochastic signatures of minute fluctuations in overt movements during a visuomotor task. Consequently, a large gap exists between the body’s manifestations of mental states and their descriptions, creating a disembodied approach in the psychological and neural sciences: contributions of the peripheral nervous system to central control, executive functions, and decision-making processes are poorly understood. In marked contrast, the psychological and psychiatric arenas mainly rely on verbal descriptions and interpretations of behavior via observation. Recently, movement variability has been of great interest to motor control physiologists as it constitutes a physical, quantifiable form of sensory feedback to aid in planning, updating, and executing complex actions.
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