IMPORTANCE OF VISUAL INFORMATION AT CHANGE IN MOTION DIRECTION ON DEPTH PERCEPTION

This paper demonstrates the importance of visual information on depth perception from monocular motion parallax presented at the time of change in the motion direction of head and stimulus movements. In head-tracking systems, a longer delay time between the head and stimulus movements degrades the depth perception from monocular motion parallax. Because this delay is noticeable at this time, we hypothesized that the visual information given at the time of the direction change plays a critical role in the depth perception from motion parallax. We evaluated depth perception from monocular motion parallax with and without a visual stimulus at the time of the motion direction change to confirm our hypothesis, and clarified that stable and unambiguous depth can be perceived by presenting the change of the stimulus motion direction. We also demonstrated that it is the change in motion direction itself that is important rather than the temporal stop between deceleration and acceleration of the stimulus motion

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Exactly Sparse Delayed-State Filters for View-Based SLAM

This paper reports the novel insight that the simultaneous localization and mapping (SLAM) information matrix is exactly sparse in a delayed-state framework. Such a framework is used in view-based representations of the environment that rely upon scan-matching raw sensor data to obtain virtual observations of robot motion with respect to a place it has previously been. The exact sparseness of the delayed-state information matrix is in contrast to other recent feature-based SLAM information algorithms, such as sparse extended information filter or thin junction-tree filter, since these methods have to make approximations in order to force the feature-based SLAM information matrix to be sparse. The benefit of the exact sparsity of the delayed-state framework is that it allows one to take advantage of the information space parameterization without incurring any sparse approximation error. Therefore, it can produce equivalent results to the full-covariance solution. The approach is validated experimentally using monocular imagery for two datasets: a test-tank experiment with ground truth, and a remotely operated vehicle survey of the RMS Titanic.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86062/1/reustice-25.pd

The Effect of an Occluder on the Accuracy of Depth Perception in Optical See-Through Augmented Reality

Three experiments were conducted to study the effect of an occluder on the accuracy of nearield depth perception in optical-see-through augmented reality (AR). The first experiment was a duplicate experiment of the one in Edwards et al. [2004]. We found more accurate results than Edwards et al.’s work and did not find the occluder’s main effect or its two-way interaction effect with distance on the accuracy of observers’ depth matching. The second experiment was an updated version of the first one using a within-subject design and a more accurate calibration method. The results were that errors ranged from –5 to 3 mm when the occluder was present, –3 to 2 mm when the occluder was absent, and observers judged the virtual object to be closer after the presentation of the occluder. The third experiment was conducted on three subjects who were depth perception researchers. The result showed significant individual effects

Near-Field Depth Perception in Optical See-Though Augmented Reality

Augmented reality (AR) is a very promising display technology with many compelling industrial applications. However, before it can be used in actual settings, its fidelity needs to be investigated from a user-centric viewpoint. More specifically, how distance to the virtual objects is perceived in augmented reality is still an open question. To the best of our knowledge, there are only four previous studies that specifically studied distance perception in AR within reaching distances. Therefore, distance perception in augmented reality still remains a largely understudied phenomenon. This document presents research in depth perception in augmented reality in the near visual field. The specific goal of this research is to empirically study various measurement techniques for depth perception, and to study various factors that affect depth perception in augmented reality, specifically, eye accommodation, brightness, and participant age. This document discusses five experiments that have already been conducted. Experiment I aimed to determine if there are inherent difference between the perception of virtual and real objects by comparing depth judgments using two complementary distance judgment protocols: perceptual matching and blind reaching. This experiment found that real objects are perceived more accurately than virtual objects and matching is a relatively more accurate distance measure than reaching. Experiment II compared the two distance judgment protocols in the real world and augmented reality environments, with improved proprioceptive and visual feedback. This experiment found that reaching responses in the AR environment became more accurate with improved feedback. Experiment III studied the effect of different levels of accommodative demand (collimated, consistent, and midpoint) on distance judgments. This experiment found nearly accurate distance responses in the consistent and midpoint conditions, and a linear increase in error in the collimated condition. Experiment IV studied the effect of brightness of the target object on depth judgments. This experiment found that distance responses were shifted towards background for the dim AR target. Lastly, Experiment V studied the effect of participant age on depth judgments and found that older participants judged distance more accurately than younger participants. Taken together, these five experiments will help us understand how depth perception operates in augmented reality

Near-Field Depth Perception in Optical See-Though Augmented Reality

Augmented reality (AR) is a very promising display technology with many compelling industrial applications. However, before it can be used in actual settings, its fidelity needs to be investigated from a user-centric viewpoint. More specifically, how distance to the virtual objects is perceived in augmented reality is still an open question. To the best of our knowledge, there are only four previous studies that specifically studied distance perception in AR within reaching distances. Therefore, distance perception in augmented reality still remains a largely understudied phenomenon. This document presents research in depth perception in augmented reality in the near visual field. The specific goal of this research is to empirically study various measurement techniques for depth perception, and to study various factors that affect depth perception in augmented reality, specifically, eye accommodation, brightness, and participant age. This document discusses five experiments that have already been conducted. Experiment I aimed to determine if there are inherent difference between the perception of virtual and real objects by comparing depth judgments using two complementary distance judgment protocols: perceptual matching and blind reaching. This experiment found that real objects are perceived more accurately than virtual objects and matching is a relatively more accurate distance measure than reaching. Experiment II compared the two distance judgment protocols in the real world and augmented reality environments, with improved proprioceptive and visual feedback. This experiment found that reaching responses in the AR environment became more accurate with improved feedback. Experiment III studied the effect of different levels of accommodative demand (collimated, consistent, and midpoint) on distance judgments. This experiment found nearly accurate distance responses in the consistent and midpoint conditions, and a linear increase in error in the collimated condition. Experiment IV studied the effect of brightness of the target object on depth judgments. This experiment found that distance responses were shifted towards background for the dim AR target. Lastly, Experiment V studied the effect of participant age on depth judgments and found that older participants judged distance more accurately than younger participants. Taken together, these five experiments will help us understand how depth perception operates in augmented reality

Shaped-based IMU/Camera Tightly Coupled Object-level SLAM using Rao-Blackwellized Particle Filtering

Simultaneous Localization and Mapping (SLAM) is a decades-old problem. The classical solution to this problem utilizes entities such as feature points that cannot facilitate the interactions between a robot and its environment (e.g., grabbing objects). Recent advances in deep learning have paved the way to accurately detect objects in the image under various illumination conditions and occlusions. This led to the emergence of object-level solutions to the SLAM problem. Current object-level methods depend on an initial solution using classical approaches and assume that errors are Gaussian. This research develops a standalone solution to object-level SLAM that integrates the data from a monocular camera and an IMU (available in low-end devices) using Rao Blackwellized Particle Filter (RBPF). RBPF does not assume Gaussian distribution for the error; thus, it can handle a variety of scenarios (such as when a symmetrical object with pose ambiguities is encountered). The developed method utilizes shape instead of texture; therefore, texture-less objects can be incorporated into the solution. In the particle weighing process, a new method is developed that utilizes the Intersection over the Union (IoU) area of the observed and projected boundaries of the object that does not require point-to-point correspondence. Thus, it is not prone to false data correspondences. Landmark initialization is another important challenge for object-level SLAM. In the state-of-the-art delayed initialization, the trajectory estimation only relies on the motion model provided by IMU mechanization (during the initialization), leading to large errors. In this thesis, two novel undelayed initializations are developed. One relies only on a monocular camera and IMU, and the other utilizes an ultrasonic rangefinder as well. The developed object-level SLAM is tested using wheeled robots and handheld devices, and an error (in the position) of 4.1 to 13.1 cm (0.005 to 0.028 of the total path length) has been obtained through extensive experiments using only a single object. These experiments are conducted in different indoor environments under different conditions (e.g. illumination). Further, it is shown that undelayed initialization using an ultrasonic sensor can reduce the algorithm's runtime by half