Evaluative cognition and attention allocation in human interface

Matsui, Nobuyuki; Bamba, Eiichi

doi:10.1002/scj.4690191108

Cited by 4 publications

(8 citation statements)

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“…Based on the above work, Matsui researched attention allocation using fuzzy theory and quantified the selective attention mechanism of the information using hybrid entropy [41,42]. Wanyan et al [15] and Wu et al [16] applied detection efficiency factors and fatigue factors to Matsui's fuzzy model for pilots.…”

Section: Related Workmentioning

confidence: 99%

“…The comprehensive consideration of the theory aimed to maximize the acquisition of the important information and minimize the fuzziness of the scene. The above attention allocation models based on fuzzy theory usually involved two main factors: information value and information fuzziness [15][16][17]41,42].…”

Section: Related Workmentioning

confidence: 99%

“…The proposed attention allocation model was built based on the work of Matsui's and Wanyan et al's models [15,16,42]. The information value is presented by the proposed value priority function using the membership degrees of the importance and information amounts.…”

Section: Related Workmentioning

confidence: 99%

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Supervisors’ Visual Attention Allocation Modeling Using Hybrid Entropy

Bao

Fang

Guo

et al. 2019

Entropy

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With the improvement in automation technology, humans have now become supervisors of the complicated control systems that monitor the informative human–machine interface. Analyzing the visual attention allocation behaviors of supervisors is essential for the design and evaluation of the interface. Supervisors tend to pay attention to visual sections with information with more fuzziness, which makes themselves have a higher mental entropy. Supervisors tend to focus on the important information in the interface. In this paper, the fuzziness tendency is described by the probability of correct evaluation of the visual sections using hybrid entropy. The importance tendency is defined by the proposed value priority function. The function is based on the definition of the amount of information using the membership degrees of the importance. By combining these two cognitive tendencies, the informative top-down visual attention allocation mechanism was revealed, and the supervisors’ visual attention allocation model was built. The Building Automatic System (BAS) was used to monitor the environmental equipment in a subway, which is a typical informative human–machine interface. An experiment using the BAS simulator was conducted to verify the model. The results showed that the supervisor’s attention behavior was in good agreement with the proposed model. The effectiveness and comparison with the current models were also discussed. The proposed attention allocation model is effective and reasonable, which is promising for use in behavior analysis, cognitive optimization, and industrial design.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Supervisors’ Visual Attention Allocation Modeling Using Hybrid Entropy

Bao

Fang

Guo

et al. 2019

Entropy

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“…Another point is to examine the "strength* of the association. For this purpose, the following two sets of simple figures are used as the image information: (1) figures with shapes with relatively strong potential association to the score, such as { x X , x, A, 0, e}; and (ii) figures with shapes with relatively weak potential association to the score, such as { 4 X , A, 0, 0). For those sets of simple figures, it is relatively easy to recall the allocation of scores.…”

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confidence: 99%

Fractal dependence of texture perception

Matsui¹,

Tsuruno²,

Bamba³

1994

Systems & Computers in Japan

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SUMMARYHumans can easily discriminate not only simple figures but also similar complex textures. At present, a large information processing capability is required for a machine to process such texture image information in a short time on the CRT screen or medical images.It is important to analyze the visual information mechanism for those images.In recent studies of visual search, the texton is considered as apop-out discrimination element. There remain a number of problems in the recognition of the texture composed of complex patterns such that the texton in not clear. On the other hand, fractal can be a measure for the complexity, and is related closely to the visual system. This paper presents a recognition experiment and an attention allocation model by simultaneous presentation of multiple images, where a set of textures with known fractal dimensions are used as the image information. The relations are examined quantitatively. As 82 a result, it is shown that a relation can be assumed between the fractal dimension (Dp, DH) of the texture and the allocation of attention& to the texture. For the set (A) of textures, a multiple regression expression f(A) = 97.6 + 20.1 Dp -55.3 DH can be applied with a high correlation coefficient. Thus, it is verified that the fractal information can be used as the pop-out discrimination element in the recognition of the texture.

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“…uliile driving 11 car. And there lkippcn some car accidents that are caused by the use of the cellular phone.…”

mentioning

confidence: 99%

An analysis of human error in skill task and visual recognition under auditory interruption

Sugimoto

Toyabe

Sato

1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation

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When \\e drive a car. rve have to do different kinds of works siniultaneously. and thus \ve are apt to make some errors under such simultaneous ivorks. In recent years.there have been many dri1w-s who use a cellular phone uliile driving 11 car. And there lkippcn some car accidents that are caused by the use of the cellular phone. This kind of accidents has become one of the social problems today. To use of a hands-free phone is efficient to free the driver from tlie operation of a cellular phone or from looking aside while driving. which may cause an accident. However. there is a critical possibilih for the driver to lose his attention and misjudge. even if he uses a handsfree phone. This might be said to be a kind of a hidden dangerous phenomenon. When a driver communicates with someone by :i phone. he has to do tluee extra works that he does not need to do in a usual driving. One of them is to listen to and to understand the person whom he is talking to. and the second is to think of the answer to h i . and the third is to talk to him.Iiii our research experiment we have set an experimental environment consisting of tluee tasks on a computer screen to quantitatively analyze mutual effect of these tasks. The first task is a tracking task. wldch is a typical skill base one. The second task is to recognize the visual information that is indicated by four different media on a computer screen and to respond as soon as possible. The third task is to listen to a conversation and auswer a question about the conversatioii. This task is supposed to be the same as using a cellular phone while driving a car.I n this paper we have exanuned the effect of third task on tlie first and tlie second tasks. There \vas not any effect of the third task on the perforniance of the tracking task. The time needed to respond after getting the information n n s affected a little by tlie third task. The number of o\.erlooking tlie visual information in the second task significantly increased by the effect of the third task. This point might be one of the causes that result in a car accident

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Evaluative cognition and attention allocation in human interface

Cited by 4 publications

References 3 publications

Supervisors’ Visual Attention Allocation Modeling Using Hybrid Entropy

Supervisors’ Visual Attention Allocation Modeling Using Hybrid Entropy

Fractal dependence of texture perception

An analysis of human error in skill task and visual recognition under auditory interruption

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