Information Processing in Visual System - Optical Illusion and Visual Mechanism

2001 ◽  
Vol 13 (6) ◽  
pp. 569-574
Author(s):  
Masanori Idesawa ◽  
Keyword(s):  
Information Processing ◽  
Visual System ◽  
Visual Function ◽  
External World ◽  
Automated System ◽  
Human Beings ◽  
Optical Illusion ◽  
Optical Illusions ◽  
Visual Mechanism ◽  
Human Visual Mechanism

Human beings obtain big amount of information from the external world through their visual system. Automated system such as robot must provide the visual functions for their flexible operations in 3-D circumstances. In order to realize the visual function artificially, we would be better to learn from the human visual mechanism. Optical illusions would be a pure reflection of the human visual mechanism; they can be used for investigating human visual mechanism. New types of optical illusion with binocular viewing are introduced and investigated.

A Study on Visual Mechanism with Optical Illusions

1997 ◽  
Vol 9 (2) ◽  
pp. 85-91 ◽  
Author(s):  
Masanori Idesawa ◽  
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Visual Stimuli ◽  
Close Relation ◽  
Depth Information ◽  
Optical Illusions ◽  
System A ◽  
Visual Mechanism ◽  
Human Visual Mechanism ◽  
Processing Techniques

Optical illusion seems to be the phenomena which are purely reflecting the mechanism of.human visual system and are expected as the effective cues to elucidating human visual mechanism. The author found the new types of 3-D visual illusion with binocular viewing. From the visual stimuli of binocular disparity given only along the contour of an object, human visual system can perceive entire 3-D illusory object where there are no physical visual stimuli giving depth information. They have close relation with the 3-D space perceiving functions in the human visual system. A study on these newly found optical illusions are introduced and the considerations are made for their applications and the exploitations including the contributions of information processing techniques such as computer graphics, computer vision and so on.

scholarly journals Management of Abnormal Visual Developments

2021 ◽  
Author(s):  
Longqian Liu ◽  
Xiaohang Chen ◽  
Pengfan Chen ◽  
Yifan Wu ◽  
Jianglan Wang ◽  
...  
Keyword(s):  
Visual Acuity ◽  
Visual System ◽  
Refractive Error ◽  
Visual Function ◽  
Visual Experience ◽  
External World ◽  
Visual Development ◽  
Human Beings ◽  
Good Visual Acuity ◽  
Abnormal Visual

When human beings recognize the external world, more than 80% of the information come from visual function and visual system. Normal visual development and normal binocularity are the fundamental of good visual acuity and visual functions. Any abnormal visual experience would cause abnormality, such as refractive error, strabismus, amblyopia and other diseases. The patients with abnormal visual developments were reported to have abnormal, lonely, and other psycho problems. In this chapter, we will describe the normal developmental of visual function, summarize the abnormal developments and the correction or treatment.

Perceptual Illusions in Imagery

1998 ◽  
Vol 3 (4) ◽  
pp. 281-288 ◽  
Author(s):  
Fiorella Giusberti ◽  
Cesare Cornoldi ◽  
Rossana De Beni ◽  
Manfredo Massironi
Keyword(s):  
Information Processing ◽  
Visual Information ◽  
Mental Image ◽  
Ponzo Illusion ◽  
Optical Illusion ◽  
Imagery Condition ◽  
Optical Illusions ◽  
Perceptual Illusions ◽  
Perception Condition ◽  
Early Phases

A mental image is in many ways analogous to a percept but it is not completely identical to it. In some respects, visual perception and visual imagery work in different ways. One area which is worth examining with regard to similarities and asymmetries between perception and imagery is the initial phases of visual information processing. The literature includes some references to the equivalence of imagery and perception in optical illusions, but data are contradictory. In our view, a mental image should not be particularly sensitive to variables which are critical in producing an optical illusion, i.e., variables affecting the early phases of information processing and field global effects. Our hypothesis is that an optical illusion will be present in a perception condition but not in an equivalent imagery condition. To test this, we carried out two experiments using the Ebbinghaus illusion and the Ponzo illusion. The results confirmed our hypothesis, demonstrating that there are indeed asymmetries between perception and imagery and that such differences mainly concern specific perceptual processes that differ from those involved in the generation of a mental image.

scholarly journals Difference in Recognition of Optical Illusion Using Visual and Tactual Sense

1992 ◽  
Vol 4 (1) ◽  
pp. 58-62 ◽  
Author(s):  
Yukio Fukui ◽  
◽  
Makoto Shimojo
Keyword(s):  
Visual System ◽  
Interface Design ◽  
Visual Recognition ◽  
Force Feedback ◽  
Visual Display ◽  
Optical Illusion ◽  
Optical Illusions ◽  
Interactive Interface ◽  
Haptic Exploration ◽  
The Subject

In addition to visual display, force-feedback will play an important role in interactive interface design for computers. Although the human visual system is generally more sensitive than haptics, the visual system is subject to optical illusions. In this study, we have conducted experiments to obtain visual and/or haptical sensitivity of recognition of the features of figures, such as the deformation of a circle or the bend of a line, under optical illusion. It was found that the figure which the subject judges to be a true circle or a line without bend is closer to the true figure, when using haptic exploration compared to that chosen by visual recognition. However, the probable error by haptics is larger than that by vision. Recognition using both haptics and vision causes conflict because of optical illusion, resulting in almost the same amount of errors as by vision alone.

IMITATING HUMAN VISUAL ATTENTION AND REPRODUCING OPTICAL ILLUSIONS BY ANT SCAN

2003 ◽  
Vol 03 (02) ◽  
pp. 157-166 ◽  
Author(s):  
UGO VALLONE ◽  
ALAIN MÉRIGOT
Keyword(s):  
Visual Attention ◽  
Human Beings ◽  
Optical Illusion ◽  
Qualitative Explanation ◽  
New Agents ◽  
Optical Illusions ◽  
Emergent Phenomenon ◽  
New Strategy ◽  
Static Images ◽  
Human Visual Attention

This article describes a new strategy for analyzing contours in static images. The goal of this analysis is to find the interest centres in the images and then to explain some common optical illusion phenomena. The approach proposed is based on a modified version of the Ant Colony Optimization paradigm named Ant Scan (here introduced). Ant Scan is different from the ACO meta-heuristic principally in the mechanism of exploration of the interest space (the image to be analyzed). Experimental results have shown that interactions among these new agents (based on communication by pheromone) can generate another type of emergent phenomenon that can be utilized to explain how human beings process static images. Classical optical illusions have been analyzed with this new model and a qualitative explanation of how they act is provided.

scholarly journals Structured Computational Modeling of Human Visual System for No-reference Image Quality Assessment

2021 ◽  
Author(s):  
Wen-Han Zhu ◽  
Wei Sun ◽  
Xiong-Kuo Min ◽  
Guang-Tao Zhai ◽  
Xiao-Kang Yang
Keyword(s):  
Information Processing ◽  
Image Quality ◽  
Visual System ◽  
Computational Modeling ◽  
Quality Assessment ◽  
Human Visual System ◽  
Visual Communication ◽  
Visual Experience ◽  
Image Quality Assessment ◽  
Model Based

AbstractObjective image quality assessment (IQA) plays an important role in various visual communication systems, which can automatically and efficiently predict the perceived quality of images. The human eye is the ultimate evaluator for visual experience, thus the modeling of human visual system (HVS) is a core issue for objective IQA and visual experience optimization. The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively, while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity. For bridging the gap between signal distortion and visual experience, in this paper, we propose a novel perceptual no-reference (NR) IQA algorithm based on structural computational modeling of HVS. According to the mechanism of the human brain, we divide the visual signal processing into a low-level visual layer, a middle-level visual layer and a high-level visual layer, which conduct pixel information processing, primitive information processing and global image information processing, respectively. The natural scene statistics (NSS) based features, deep features and free-energy based features are extracted from these three layers. The support vector regression (SVR) is employed to aggregate features to the final quality prediction. Extensive experimental comparisons on three widely used benchmark IQA databases (LIVE, CSIQ and TID2013) demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.

The perception of humanness in conversational journalism: An algorithmic information-processing perspective

2021 ◽  
pp. 146144482199380
Author(s):  
Donghee Shin
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Cognitive Model ◽  
Human Beings ◽  
User Perception ◽  
User Experiences ◽  
Step Flow ◽  
Algorithmic Information ◽  
Information Processing Perspective ◽  
Practical Implications

How much do anthropomorphisms influence the perception of users about whether they are conversing with a human or an algorithm in a chatbot environment? We develop a cognitive model using the constructs of anthropomorphism and explainability to explain user experiences with conversational journalism (CJ) in the context of chatbot news. We examine how users perceive anthropomorphic and explanatory cues, and how these stimuli influence user perception of and attitudes toward CJ. Anthropomorphic explanations of why and how certain items are recommended afford users a sense of humanness, which then affects trust and emotional assurance. Perceived humanness triggers a two-step flow of interaction by defining the baseline to make a judgment about the qualities of CJ and by affording the capacity to interact with chatbots concerning their intention to interact with chatbots. We develop practical implications relevant to chatbots and ascertain the significance of humanness as a social cue in CJ. We offer a theoretical lens through which to characterize humanness as a key mechanism of human–artificial intelligence (AI) interaction, of which the eventual goal is humans perceive AI as human beings. Our results help to better understand human–chatbot interaction in CJ by illustrating how humans interact with chatbots and explaining why humans accept the way of CJ.

Visual control of orientation behaviour in the fly: Part I. A quantitative analysis

1976 ◽  
Vol 9 (3) ◽  
pp. 311-375 ◽  
Author(s):  
Werner Reichardt ◽  
Tomaso Poggio
Keyword(s):  
Information Processing ◽  
Quantitative Analysis ◽  
Visual System ◽  
Sensory Information ◽  
Model Systems ◽  
Suitable Model ◽  
Logical Organization ◽  
Integrative Level ◽  
Processing Properties ◽  
Different Levels

An understanding of sensory information processing in the nervous system will probably require investigations with a variety of ‘model’ systems at different levels of complexity.Our choice of a suitable model system was constrained by two conflicting requirements: on one hand the information processing properties of the system should be rather complex, on the other hand the system should be amenable to a quantitative analysis. In this sense the fly represents a compromise.In these two papers we explore how optical information is processed by the fly's visual system. Our objective is to unravel the logical organization of the fly's visual system and its underlying functional and computational principles. Our approach is at a highly integrative level. There are different levels of analysing and ‘understanding’ complex systems, like a brain or a sophisticated computer.

Man, Monkey, and Blindsight

1998 ◽  
Vol 4 (4) ◽  
pp. 227-230 ◽  
Author(s):  
Tirin Moore ◽  
Hillary R. Rodman ◽  
Charles G. Gross
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Visual Function ◽  
Forced Choice ◽  
Neural Mechanisms ◽  
Residual Vision ◽  
Choice Testing

The visual function that survives damage to the primary visual cortex (V1) in humans is often unaccompanied by awareness. This type of residual vision, called “blindsight,” has raised considerable interest because it implies a separation of conscious from unconscious vision mechanisms. The monkey visual system has proven to be a useful model in elucidating the possible neural mechanisms of residual vision and blindsight in humans. Clear similarities, however, between the phenomenology of human and monkey residual vision have only recently become evident. This article summarizes parallels between residual vision in monkeys and humans with damage to V1. These parallels Include the tendency of the remaining vision to require forced-choice testing and the fact that more robust residual vision remains when V1 damage is sustained early in life. NEUROSCIENTIST 4:227–230

Learning Algorithms for Anomaly Detection from Images

Biometrics ◽  
2017 ◽  
pp. 281-308
Author(s):  
Tarem Ahmed ◽  
Al-Sakib Khan Pathan ◽  
Supriyo Shafkat Ahmed
Keyword(s):  
Human Security ◽  
Visual Surveillance ◽  
Automated System ◽  
Surveillance Systems ◽  
Human Beings ◽  
Security Officer ◽  
Security Officers ◽  
Large Numbers ◽  
Quantitative Performance ◽  
Present World

Visual surveillance networks are installed in many sensitive places in the present world. Human security officers are required to continuously stare at large numbers of monitors simultaneously, and for lengths of time at a stretch. Constant alert vigilance for hours on end is difficult to maintain for human beings. It is thus important to remove the onus of detecting unwanted activity from the human security officer to an automated system. While many researchers have proposed solutions to this problem in the recent past, significant gaps remain in existing knowledge. Most existing algorithms involve high complexities. No quantitative performance analysis is provided by most researchers. Most commercial systems require expensive equipment. This work proposes algorithms where the complexities are independent of time, making the algorithms naturally suited to online use. In addition, the proposed methods have been shown to work with the simplest surveillance systems that may already be publicly deployed. Furthermore, direct quantitative performance comparisons are provided.

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