scholarly journals Looking for Image Statistics: Active Vision With Avatars in a Naturalistic Virtual Environment

2021 ◽  
Vol 12 ◽  
Author(s):  
Dominik Straub ◽  
Constantin A. Rothkopf
Keyword(s):  
Visual Field ◽  
Visual System ◽  
Physical Properties ◽  
Virtual Environment ◽  
Image Databases ◽  
Field Of View ◽  
Natural Image ◽  
Image Statistics ◽  
Neural Representations ◽  
Visual Behaviors

The efficient coding hypothesis posits that sensory systems are tuned to the regularities of their natural input. The statistics of natural image databases have been the topic of many studies, which have revealed biases in the distribution of orientations that are related to neural representations as well as behavior in psychophysical tasks. However, commonly used natural image databases contain images taken with a camera with a planar image sensor and limited field of view. Thus, these images do not incorporate the physical properties of the visual system and its active use reflecting body and eye movements. Here, we investigate quantitatively, whether the active use of the visual system influences image statistics across the visual field by simulating visual behaviors in an avatar in a naturalistic virtual environment. Images with a field of view of 120° were generated during exploration of a virtual forest environment both for a human and cat avatar. The physical properties of the visual system were taken into account by projecting the images onto idealized retinas according to models of the eyes' geometrical optics. Crucially, different active gaze behaviors were simulated to obtain image ensembles that allow investigating the consequences of active visual behaviors on the statistics of the input to the visual system. In the central visual field, the statistics of the virtual images matched photographic images regarding their power spectra and a bias in edge orientations toward cardinal directions. At larger eccentricities, the cardinal bias was superimposed with a gradually increasing radial bias. The strength of this effect depends on the active visual behavior and the physical properties of the eye. There were also significant differences between the upper and lower visual field, which became stronger depending on how the environment was actively sampled. Taken together, the results show that quantitatively relating natural image statistics to neural representations and psychophysical behavior requires not only to take the structure of the environment into account, but also the physical properties of the visual system, and its active use in behavior.

scholarly journals Field of View and Skill Training of Table Tennis Teaching Based on Virtual Environment Technology

2016 ◽  
Vol 11 (11) ◽  
pp. 60
Author(s):  
Li Li
Keyword(s):  
Visual Field ◽  
Virtual Environment ◽  
Skill Training ◽  
Teaching Quality ◽  
Field Of View ◽  
Table Tennis ◽  
Field Training

Focusing on the topic of improving the table tennis teaching quality with the visual field training, the test is to grab images repeatedly by using a camera in a speed of 119s, and the final result shows that it gets the correct hitting points on racket coordinating with correct racket angles, which verifies the effectiveness of the visual field training. Finally, it's concluded that the visual field training can improve the athletes' abilities of focus and judgment, and enhance their exercise stability.

Characteristics of Visual Fidelity in the Virtual Environment

1996 ◽  
Vol 5 (3) ◽  
pp. 330-345 ◽  
Author(s):  
Edward J. Rinalducci
Keyword(s):  
Visual System ◽  
Virtual Environments ◽  
Virtual Environment ◽  
Spatial Resolution ◽  
Visual Cues ◽  
Field Of View ◽  
Visual Characteristics ◽  
The Creation ◽  
Vertical Development ◽  
Visual Fidelity

This paper provides an overview of the literature on the visual system, placing special emphasis on those visual characteristics regarded as necessary to produce adequate visual fidelity in virtual environments. These visual cues apply to the creation of various virtual environments including those involving flying, driving, sailing, or walking. A variety of cues are examined, in particular, motion, color, stereopsis, pictorial and secondary cues, physiological cues, texture, vertical development, luminance, field-of-view, and spatial resolution. Conclusions and recommendations for research are also presented.

scholarly journals Systematic differences between visually-relevant global and local image statistics of brain MRI and natural scenes

2018 ◽  
Author(s):  
Yueyang Xu ◽  
Ashish Raj ◽  
Jonathan Victor ◽  
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Image Formation ◽  
Natural Images ◽  
Natural Image ◽  
Natural Scenes ◽  
Image Statistics ◽  
Processing Technologies ◽  
Global And Local ◽  
Local Image

AbstractAn important heuristic in developing image processing technologies is to mimic the computational strategies used by humans. Relevant to this, recent studies have shown that the human brain’s processing strategy is closely matched to the characteristics of natural scenes, both in terms of global and local image statistics. However, structural MRI images and natural scenes have fundamental differences: the former are two-dimensional sections through a volume, the latter are projections. MRI image formation is also radically different from natural image formation, involving acquisition in Fourier space, followed by several filtering and processing steps that all have the potential to alter image statistics. As a consequence, aspects of the human visual system that are finely-tuned to processing natural scenes may not be equally well-suited for MRI images, and identification of the differences between MRI images and natural scenes may lead to improved machine analysis of MRI.With these considerations in mind, we analyzed spectra and local image statistics of MRI images in several databases including T1 and FLAIR sequence types and of simulated MRI images,[1]–[6] and compared this analysis to a parallel analysis of natural images[7] and visual sensitivity[7][8]. We found substantial differences between the statistical features of MRI images and natural images. Power spectra of MRI images had a steeper slope than that of natural images, indicating a lack of scale invariance. Independent of this, local image statistics of MRI and natural images differed: compared to natural images, MRI images had smaller variations in their local two-point statistics and larger variations in their local three-point statistics – to which the human visual system is relatively insensitive. Our findings were consistent across MRI databases and simulated MRI images, suggesting that they result from brain geometry at the scale of MRI resolution, rather than characteristics of specific imaging and reconstruction methods.

scholarly journals Natural Image Statistics for Mouse Vision

2021 ◽  
Author(s):  
Luca Abballe ◽  
Hiroki Asari
Keyword(s):  
Visual Field ◽  
Uv Light ◽  
Green Light ◽  
Mouse Retina ◽  
Natural Image ◽  
Natural Scenes ◽  
Lower Visual Field ◽  
Local Contrast ◽  
Natural Image Statistics ◽  
Image Statistics

The mouse has dichromatic colour vision based on two different types of opsins: short (S)-and middle (M)-wavelength-sensitive opsins with peak sensitivity to ultraviolet (UV; 360 nm) and green light (508 nm), respectively. In the mouse retina, the cone photoreceptors that predominantly express the S-opsin are more sensitive to contrasts, and denser towards the ventral retina, preferentially sampling the upper part of the visual field. In contrast, the expression of the M-opsin gradually increases towards the dorsal retina that encodes the lower visual field. Such distinct retinal organizations are assumed to arise from a selective pressure in evolution to efficiently encode the natural scenes. However, natural image statistics of UV light have never been examined beyond the spectral analysis. Here we developed a multi-spectral camera and examined the UV and green image statistics of the same natural scenes. We found that the local contrast and the spatial correlation were higher in UV than in green for images above the horizon, but lower in UV than in green for those below the horizon. This suggests that the mouse retina is not necessarily optimal for maximizing the bandwidth of information transmission. Factors besides the coding efficiency, such as visual behavioural requirements, will thus need to be considered to fully explain the characteristic organization of the mouse retina.

Natural image statistics in the dorsal and ventral visual field match a switch in flight behaviour of a hawkmoth

2021 ◽  
Vol 31 (6) ◽  
pp. R280-R281
Author(s):  
Ronja Bigge ◽  
Maximilian Pfefferle ◽  
Keram Pfeiffer ◽  
Anna Stöckl
Keyword(s):  
Visual Field ◽  
Natural Image ◽  
Natural Image Statistics ◽  
Flight Behaviour ◽  
Image Statistics

On Why Objects Appear Smaller in the Visual Periphery

2019 ◽  
Vol 31 (1) ◽  
pp. 88-96 ◽  
Author(s):  
Wladimir Kirsch ◽  
Roland Pfister ◽  
Wilfried Kunde
Keyword(s):  
Visual Field ◽  
Visual System ◽  
Structural Properties ◽  
Spatial Attention ◽  
Visuospatial Attention ◽  
Peripheral Target ◽  
Perceptual Distortion ◽  
Visual Periphery ◽  
Peripheral Location ◽  
Exogenous Cue

An object appears smaller in the periphery than in the center of the visual field. In two experiments ( N = 24), we demonstrated that visuospatial attention contributes substantially to this perceptual distortion. Participants judged the size of central and peripheral target objects after a transient, exogenous cue directed their attention to either the central or the peripheral location. Peripheral target objects were judged to be smaller following a central cue, whereas this effect disappeared completely when the peripheral target was cued. This outcome suggests that objects appear smaller in the visual periphery not only because of the structural properties of the visual system but also because of a lack of spatial attention.

scholarly journals Vision as oculomotor reward: cognitive contributions to the dynamic control of saccadic eye movements

2021 ◽  
Author(s):  
Christian Wolf ◽  
Markus Lappe
Keyword(s):  
Eye Movements ◽  
Visual Field ◽  
Visual System ◽  
Dynamic Control ◽  
Saccadic Eye Movements ◽  
Saccade Target ◽  
Cognitive Mechanisms ◽  
Foveal Vision ◽  
Subsequent Behavior ◽  
High Level

AbstractHumans and other primates are equipped with a foveated visual system. As a consequence, we reorient our fovea to objects and targets in the visual field that are conspicuous or that we consider relevant or worth looking at. These reorientations are achieved by means of saccadic eye movements. Where we saccade to depends on various low-level factors such as a targets’ luminance but also crucially on high-level factors like the expected reward or a targets’ relevance for perception and subsequent behavior. Here, we review recent findings how the control of saccadic eye movements is influenced by higher-level cognitive processes. We first describe the pathways by which cognitive contributions can influence the neural oculomotor circuit. Second, we summarize what saccade parameters reveal about cognitive mechanisms, particularly saccade latencies, saccade kinematics and changes in saccade gain. Finally, we review findings on what renders a saccade target valuable, as reflected in oculomotor behavior. We emphasize that foveal vision of the target after the saccade can constitute an internal reward for the visual system and that this is reflected in oculomotor dynamics that serve to quickly and accurately provide detailed foveal vision of relevant targets in the visual field.

scholarly journals A novel edge gradient algorithm for multiple mobile robots cooperative mapping in unknown environment

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986038
Author(s):  
Huang Yiqing ◽  
Wang Hui ◽  
Wei Lisheng ◽  
Gao Wengen ◽  
Ge Yuan
Keyword(s):  
Visual Field ◽  
Mobile Robots ◽  
Information Exchange ◽  
Field Of View ◽  
Gradient Algorithm ◽  
Movement Direction ◽  
Mapping Technique ◽  
Map Building ◽  
Multiple Mobile Robots ◽  
Motion Behavior

This article presented a cooperative mapping technique using a novel edge gradient algorithm for multiple mobile robots. The proposed edge gradient algorithm can be divided into four behaviors such as adjusting the movement direction, evaluating the safety of motion behavior, following behavior, and obstacle information exchange, which can effectively prevent multiple mobile robots falling into concave obstacle areas. Meanwhile, a visual field factor is constructed based on biological principles so that the mobile robots can have a larger field of view when moving away from obstacles. Also, the visual field factor will be narrowed due to the obstruction of the obstacle when approaching an obstacle and the obtained map-building data are more accurate. Finally, three sets of simulation and experimental results demonstrate the performance superiority of the presented algorithm.

The visual system of a Palaeognathous bird: Visual field, retinal topography and retino-central connections in the Chilean Tinamou (Nothoprocta perdicaria)

2014 ◽  
Vol 523 (2) ◽  
pp. 226-250 ◽  
Author(s):  
Quirin Krabichler ◽  
Tomas Vega-Zuniga ◽  
Cristian Morales ◽  
Harald Luksch ◽  
Gonzalo J. Marín
Keyword(s):  
Visual Field ◽  
Visual System ◽  
Retinal Topography ◽  
Nothoprocta Perdicaria

Towards Finding the Optimum Position in the Visual Field for a Head Worn Display Used for Task Guidance with Non-registered Graphics

2021 ◽  
Vol 5 (1) ◽  
pp. 1-26
Author(s):  
Georgianna Lin ◽  
Malcolm Haynes ◽  
Sarthak Srinivas ◽  
Pramod Kotipalli ◽  
Thad Starner
Keyword(s):  
Visual Field ◽  
Order Picking ◽  
Field Of View ◽  
Line Of Sight ◽  
Single Task ◽  
Horizontal Field ◽  
Optimum Position ◽  
Preference Task ◽  
Task Efficiency ◽  
Task Guidance

Where should a HWD be placed in a user's visual field? We present two studies that compare comfort, preference, task efficiency and accuracy for various HWD positions. The first study offsets a 9.2° horizontal field-of-view (FOV) display temporally (toward the ear) from 0° to 30° in 10° steps. 30° proves too uncomfortable while 10° is the most preferred position for a simple button-pushing game, corroborating results from previous single-task reading experiments. The second experiment uses a Magic Leap One to compare 10° x 10° FOV interfaces centered at line-of-sight, temporally offset 15° (center-right), inferiorly offset 15° (bottom-center), and offset in both directions (bottom-right) for an order picking task. The bottom-right position proved worst in terms of accuracy and several subjective metrics when compared to the line-of-sight position.

Sign in / Sign up

Export Citation Format

Share Document