• Title/Summary/Keyword: Attention System

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A New Performance Evaluation Method for Visual Attention System (시각주의 탐색 시스템을 위한 새로운 성능 평가 기법)

  • Cheoi, Kyungjoo
    • Journal of Information Technology Services
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    • v.16 no.1
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    • pp.55-72
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    • 2017
  • Many of the studies of visual attention that are currently underway are seeking ways to make application systems that can be used in practice, and obtained good results using not only simulated images but also real-world images. However, despite that previous studies of selective visual attention are models intended to implement the human vision, few experiments verified the models with actual humans and there is no standardized data nor standardized experimental method for actual images. Therefore, in this paper, we propose a new performance evaluation techniques necessary for evaluation of visual attention systems. We developed an evaluation method for evaluating the performance of the visual attention system through comparison with the results of the human experiments on visual attention. Human experiments on visual attention is an experiments where human beings are instinctively aware of the unconscious when images are given to humans. So it can be useful for evaluating performance of the bottom-up attention system. Also we propose a new selective attention system that guides the user to effectively detect ROI regions by using spatial and temporal features adaptively selected according to the input image. We evaluated the performance of proposed visual attention system through the developed performance evaluation method, and we could confirm that the results of the visual attention system are similar to those of the human visual attention.

Computer Vision System using the mechanisms of human visual attention (인간의 시각적 주의 능력을 이용한 컴퓨터 시각 시스템)

  • 최경주;이일병
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.239-242
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    • 2001
  • As systems for real time computer vision are confronted with prodigious amounts of visual information, it has become a priority to locate and analyze just that information essential to the task at hand, while ignoring the vast flow of irrelevant detail. A method of achieving this is to using human visual attention mechanism. In this paper, short review of human visual attention mechanisms and some computation models of visual attention were shown. This paper can be used as the basic data for researches on development of visual attention system that can perform various complex tasks more efficiently.

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The Neuroanatomy and Psychophysiology of Attention (집중의 신경해부와 정신생리)

  • Lee, Sung-Hoon;Park, Yun-Jo
    • Sleep Medicine and Psychophysiology
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    • v.5 no.2
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    • pp.119-133
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    • 1998
  • Attentional processes facilitate cognitive and behavioral performance in several ways. Attention serves to reduce the amount of information to receive. Attention enables humans to direct themselves to appropriate aspects of external environmental events and internal operations. Attention facilitates the selection of salient information and the allocation of cognitive processing appropriate to that information. Attention is not a unitary process that can be localized to a single neuroanatomical region. Before the cortical registration of sensory information, activation of important subcortical structures occurs, which is called as an orienting response. Once sensory information reaches the sensory cortex, a large number of perceptual processes occur, which provide various levels of perceptual resolution of the critical features of the stimuli. After this preattentional processing, information is integrated within higher cortical(heteromodal) systems in inferior parietal and temporal lobes. At this stage, the processing characteristics can be modified, and the biases of the system have a direct impact on attentional selection. Information flow has been traced through sensory analysis to a processing stage that enables the new information to be focused and modified in relation to preexisting biases. The limbic and paralimbic system play significant roles in modulating attentional response. It is labeled with affective salience and is integrated according to ongoing pressures from the motivational drive system of the hypothalamus. The salience of information greatly influences the allocation of attention. The frontal lobe operate response selection system with a reciprocal interaction with both the attention system of the parietal lobe and the limbic system. In this attentional process, the search with the spatial field is organized and a sequence of attentional responses is generated. Affective, motivational and appectitive impulses from limbic system and hypothalamus trigger response intention, preparation, planning, initiation and control of frontal lobe on this process. The reticular system, which produces ascending activation, catalyzes the overall system and increases attentional capacity. Also additional energetic pressures are created by the hypothalamus. As psychophysiological measurement, skin conductance, pupil diameter, muscle tension, heart rate, alpha wave of EEG can be used. Event related potentials also provide physiological evidence of attention during information process. NI component appears to be an electrophysiological index of selective attention. P3 response is developed during the attention related to stimulus discrimination, evaluation and response.

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Visual Attention Model Based on Particle Filter

  • Liu, Long;Wei, Wei;Li, Xianli;Pan, Yafeng;Song, Houbing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.8
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    • pp.3791-3805
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    • 2016
  • The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.

Development of Multiple-modality Psychophysical Scaling System for Evaluating Subjective User Perception of the Participatory Multimedia System (참여형 멀티미디어 시스템 사용자 감성평가를 위한 다차원 심물리학적 척도 체계)

  • Na, Jong-Gwan;Park, Min-Yong
    • Journal of the Ergonomics Society of Korea
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    • v.23 no.3
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    • pp.89-99
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    • 2004
  • A comprehensive psychophysical scaling system, multiple-modality magnitude estimation system (MMES) has been designed to measure subjective multidimensional human perception. Unlike paper-based magnitude estimation systems, the MMES has an additional auditory peripheral cue that varies with corresponding visual magnitude. As the simplest, purely psychological case, bimodal divided-attention conditions were simulated to establish the superiority of the MMES. Subjects were given brief presentations of pairs of simultaneous stimuli consisting of visual line-lengths and auditory white-noise levels. In the visual or auditory focused-attention conditions, only the line-lengths or the noise levels perceived should be reported respectively. On the other hand, in the divided-attention conditions, both the line-lengths and the noise levels should be reported. There were no significant differences among the different attention conditions. Human performance was better when the proportion of magnitude in stimulus pairs were identically presented. The additional auditory cues in the MMES improved the correlations between the magnitude of stimuli and MMES values in the divided-attention conditions.

Allocation of the skipper's attention depending on the longline fishing process of the coastal composite fishing vessel (연안복합어선의 연승조업과정에 따른 선장의 주의 배분)

  • KIM, Min-Son;HWANG, Bo-Kyu
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.58 no.2
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    • pp.175-184
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    • 2022
  • This study analyzed the allocation of the skipper's attention during fishing operation in the wheelhouse of a Korean coastal composite fishing vessel by using video observation. To summarize the results, the ratio of lookout, radar and GPS monitoring, which is essential for prevention of collision at sea, was significantly lower than that of other fishing operation due to the attention concentration on the work place during hauling line. In order to reduce exposure to risk of collisions due to concentration of attention to certain tasks such as line hauling, it is necessary to develop an alert system that can notify the approach of other ships or obstruction throughout the ship using information from radar or the automatic identification system. In addition, the order of attention allocation to devices and facilities obtained in this study is expected to be used as basic data for device or facility layout based on the principle of usage frequency in designing wheelhouse for coastal composite fishing vessels in the future.

A New Covert Visual Attention System by Object-based Spatiotemporal Cues and Their Dynamic Fusioned Saliency Map (객체기반의 시공간 단서와 이들의 동적결합 된돌출맵에 의한 상향식 인공시각주의 시스템)

  • Cheoi, Kyungjoo
    • Journal of Korea Multimedia Society
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    • v.18 no.4
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    • pp.460-472
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    • 2015
  • Most of previous visual attention system finds attention regions based on saliency map which is combined by multiple extracted features. The differences of these systems are in the methods of feature extraction and combination. This paper presents a new system which has an improvement in feature extraction method of color and motion, and in weight decision method of spatial and temporal features. Our system dynamically extracts one color which has the strongest response among two opponent colors, and detects the moving objects not moving pixels. As a combination method of spatial and temporal feature, the proposed system sets the weight dynamically by each features' relative activities. Comparative results show that our suggested feature extraction and integration method improved the detection rate of attention region.

Analysis of Effect by Duration of Cryotherapy in the Posterior region of Neck for College Students

  • Ji Hong Chang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.301-306
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    • 2023
  • Attention is a fundamental aspect in the cognitive process of human. Cognitive system of human body requires to focus on selected information among a vast amount of information from sensory organs. It has widely studied that various environmental factors affected the level of attention; however, few researches have aimed to the effect of direct cryotherapy. In this research, level of attention was studied comparing sub-indexes of FAIR test between groups with different duration of direct cryotheapy to the back of neck. FAIR test is a evaluation tool for visual attention consisting of three sub-indexes. Selective attention, accuracy of attention, and persistence of attention can be independently analyzed by FAIR test. In the analysis of selective attention, cryotherapy for 5 to 20 minutes showed higher result than cryotherapy for 40 minutes. In the analysis of persistence of attention, cryotherapy for 5 to 15 minutes showed higher result than cryotherapy for 40 minutes. Overall, selective attention and persistence of attention turns out to be maximized between 5 to 20 minutes of cryotherapy and tends to decrease afterwards. However, accuracy of attention does not seem to be affected by the duration of cryotherapy. Correlation between selective attention and the skin temperature by cryotherapy tends to be negative supporting the findings by ANOVA and post-hoc test. Correlation between persistence of attention and the skin temperature showed similar results.

Image-Based Skin Cancer Classification System Using Attention Layer (Attention layer를 활용한 이미지 기반 피부암 분류 시스템)

  • GyuWon Lee;SungHee Woo
    • Journal of Practical Engineering Education
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    • v.16 no.1_spc
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    • pp.59-64
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    • 2024
  • As the aging population grows, the incidence of cancer is increasing. Skin cancer appears externally, but people often don't notice it or simply overlook it. As a result, if the early detection period is missed, the survival rate in the case of late stage cancer is only 7.5-11%. However, the disadvantage of diagnosing, serious skin cancer is that it requires a lot of time and money, such as a detailed examination and cell tests, rather than simple visual diagnosis. To overcome these challenges, we propose an Attention-based CNN model skin cancer classification system. If skin cancer can be detected early, it can be treated quickly, and the proposed system can greatly help the work of a specialist. To mitigate the problem of image data imbalance according to skin cancer type, this skin cancer classification model applies the Over Sampling, technique to data with a high distribution ratio, and adds a pre-learning model without an Attention layer. This model is then compared to the model without the Attention layer. We also plan to solve the data imbalance problem by strengthening data augmentation techniques for specific classes.

Speaker verification system combining attention-long short term memory based speaker embedding and I-vector in far-field and noisy environments (Attention-long short term memory 기반의 화자 임베딩과 I-vector를 결합한 원거리 및 잡음 환경에서의 화자 검증 알고리즘)

  • Bae, Ara;Kim, Wooil
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.2
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    • pp.137-142
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    • 2020
  • Many studies based on I-vector have been conducted in a variety of environments, from text-dependent short-utterance to text-independent long-utterance. In this paper, we propose a speaker verification system employing a combination of I-vector with Probabilistic Linear Discriminant Analysis (PLDA) and speaker embedding of Long Short Term Memory (LSTM) with attention mechanism in far-field and noisy environments. The LSTM model's Equal Error Rate (EER) is 15.52 % and the Attention-LSTM model is 8.46 %, improving by 7.06 %. We show that the proposed method solves the problem of the existing extraction process which defines embedding as a heuristic. The EER of the I-vector/PLDA without combining is 6.18 % that shows the best performance. And combined with attention-LSTM based embedding is 2.57 % that is 3.61 % less than the baseline system, and which improves performance by 58.41 %.