• Title/Summary/Keyword: Visual attention information

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Attentional Effects of Crossmodal Spatial Display using HRTF in Target Detection Tasks (항공 목표물 탐지과제 수행에서 머리전달함수(HRTF)를 이용한 이중감각적 공간 디스플레이의 주의효과)

  • Lee, Ju-Hwan
    • Journal of Advanced Navigation Technology
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    • v.14 no.4
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    • pp.571-577
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    • 2010
  • Driving aircraft requires extremely complicated and detailed information processing. Pilots perform their tasks by selecting the information relevant to them. In this processing, spatial information presented simultaneously through crossmodal link is advantageous over the one provided in singular sensory mode. In this paper, probability to apply providing visual spatial information along with auditory information to enemy tracking system in aircraft navigation is empirically investigated. The result shows that auditory spatial information, which is virtually created through HRTF is advantageous to visual spatial information alone in attention processing. The findings suggest auditory spatial information along with visual one can be presented through crossmodal link by utilizing stereophonic sound such as HRTF. which is available in the existing simple stereo system.

Main Cause of the Interference between Visual Search and Spatial Working Memory Task (시각 탐색과 공간적 작업기억간 상호 간섭의 원인)

  • Ahn Jae-Won;Kim Min-Shik
    • Korean Journal of Cognitive Science
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    • v.16 no.3
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    • pp.155-174
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    • 2005
  • Oh and Kim (2004) and Woodman and Lurk (2004) demonstrated that spatial working memory (SWM) load Interfered concurrent visual search and that search process also impaired the maintenance of spatial information implying that visual search and SWM task both require access to the same limited-capacity mechanism. Two obvious possibilities have been suggested about what this shared limited-capacity mechanism is: common demand for attention to the locations where the items f9r the two tasks were presented (spatial attention load hypothesis), and common use of working memory to maintain a record of locations have been processed(SWM load hypothesis). To test these two hypothetical explanations, Experiment 1 replicated the mutual interference between visual search and SWM task in spite of difference of procedure with preceding researches; possible areas where the items for two tasks were presented were not separated. In Experiment 2, we presented the items for visual search either in the same quadrants where the items for SWM task had appeared (same-location rendition) or in the different quadrants (different-location condition). As a result, search efficiency was more impaired in the different-location condition than in the same-location condition. The memory accuracy was worse in the different-location rendition than in the same-location rendition. Overall results of study indicate that the mutual interference between SWM and visual search might be related to the overload of spatial attention, but not to that of SWM.

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Efficient Object Classification Scheme for Scanned Educational Book Image (교육용 도서 영상을 위한 효과적인 객체 자동 분류 기술)

  • Choi, Young-Ju;Kim, Ji-Hae;Lee, Young-Woon;Lee, Jong-Hyeok;Hong, Gwang-Soo;Kim, Byung-Gyu
    • Journal of Digital Contents Society
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    • v.18 no.7
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    • pp.1323-1331
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    • 2017
  • Despite the fact that the copyright has grown into a large-scale business, there are many constant problems especially in image copyright. In this study, we propose an automatic object extraction and classification system for the scanned educational book image by combining document image processing and intelligent information technology like deep learning. First, the proposed technology removes noise component and then performs a visual attention assessment-based region separation. Then we carry out grouping operation based on extracted block areas and categorize each block as a picture or a character area. Finally, the caption area is extracted by searching around the classified picture area. As a result of the performance evaluation, it can be seen an average accuracy of 83% in the extraction of the image and caption area. For only image region detection, up-to 97% of accuracy is verified.

3D Visual Attention Model and its Application to No-reference Stereoscopic Video Quality Assessment (3차원 시각 주의 모델과 이를 이용한 무참조 스테레오스코픽 비디오 화질 측정 방법)

  • Kim, Donghyun;Sohn, Kwanghoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.110-122
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    • 2014
  • As multimedia technologies develop, three-dimensional (3D) technologies are attracting increasing attention from researchers. In particular, video quality assessment (VQA) has become a critical issue in stereoscopic image/video processing applications. Furthermore, a human visual system (HVS) could play an important role in the measurement of stereoscopic video quality, yet existing VQA methods have done little to develop a HVS for stereoscopic video. We seek to amend this by proposing a 3D visual attention (3DVA) model which simulates the HVS for stereoscopic video by combining multiple perceptual stimuli such as depth, motion, color, intensity, and orientation contrast. We utilize this 3DVA model for pooling on significant regions of very poor video quality, and we propose no-reference (NR) stereoscopic VQA (SVQA) method. We validated the proposed SVQA method using subjective test scores from our results and those reported by others. Our approach yields high correlation with the measured mean opinion score (MOS) as well as consistent performance in asymmetric coding conditions. Additionally, the 3DVA model is used to extract information for the region-of-interest (ROI). Subjective evaluations of the extracted ROI indicate that the 3DVA-based ROI extraction outperforms the other compared extraction methods using spatial or/and temporal terms.

Detecting Object of Interest from a Noisy Image Using Human Visual Attention

  • Cheoi Kyung-Joo
    • International Journal of Contents
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    • v.2 no.1
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    • pp.5-8
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    • 2006
  • This paper describes a new mechanism of detecting object of interest from a noisy image, without using any a-priori knowledge about the target. It employs a parallel set of filters inspired upon biological findings of mammalian vision. In our proposed system, several basic features are extracted directly from original input visual stimuli, and these features are integrated based on their local competitive relations and statistical information. Through integration process, unnecessary features for detecting the target are spontaneously decreased, while useful features are enhanced. Experiments have been performed on a set of computer generated and real images corrupted with noise.

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A Saliency-Based Focusing Region Selection Method for Robust Auto-Focusing

  • Jeon, Jaehwan;Cho, Changhun;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.1 no.3
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    • pp.133-142
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    • 2012
  • This paper presents a salient region detection algorithm for auto-focusing based on the characteristics of a human's visual attention. To describe the saliency at the local, regional, and global levels, this paper proposes a set of novel features including multi-scale local contrast, variance, center-surround entropy, and closeness to the center. Those features are then prioritized to produce a saliency map. The major advantage of the proposed approach is twofold; i) robustness to changes in focus and ii) low computational complexity. The experimental results showed that the proposed method outperforms the existing low-level feature-based methods in the sense of both robustness and accuracy for auto-focusing.

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Memory in visual search: Evidence from search efficiency (시각 탐색에서의 기억: 탐색 효율성에 근거한 증거)

  • Baek Jongsoo;Kim Min-Shik
    • Korean Journal of Cognitive Science
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    • v.16 no.1
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    • pp.1-15
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    • 2005
  • Since human visual system has limited capacity for visual information processing, it should select goal-relevant information for further processing. There have been several studies that emphasized the possible involvement of memory in spatial shift of selective attention (Chun & Jiang, 1998, 1999; Klein, 1988; Klein & MacInnes, 1999). However, other studies suggested the inferiority of human visual memory in change detection(Rensink, O'Regan, & Clark, 1997; Simons & Levin, 1997) and in visual search(Hotowitz & Wolfe, 1998). The present study examined the involvement of memory in visual search; whether memory for the previously searched items guides selective attentional shift or not. We investigated how search works by comparing visual search performances in three different conditions; full exposure condition, partial exposure condition, and partial-to-full exposure condition. Revisiting searched items was allowed only in full exposure condition and not in either partial or partial-to-full exposure condition. The results showed that the efficiencies of attentional shift were nearly identical for all conditions. This finding implies that even in full exposure condition the participants scarcely re-examined the previously searched items. The results suggest that instant memory can be formed and used in visual search process. These results disagree with the earlier studies claiming thar visual search has no memory. We discussed the problems of the previous research paradigms and suggested some alternative accounts.

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Volume Haptic Rendering Algorithm for Realistic Modeling (실감형 모델링을 위한 볼륨 햅틱 렌더링 알고리즘)

  • Jung, Ji-Chan;Park, Joon-Young
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.2
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    • pp.136-143
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    • 2010
  • Realistic Modeling is to maximize the reality of the environment in which perception is made by virtual environment or remote control using two or more senses of human. Especially, the field of haptic rendering, which provides reality through interaction of visual and tactual sense in realistic model, has brought attention. Haptic rendering calculates the force caused by model deformation during interaction with a virtual model and returns it to the user. Deformable model in the haptic rendering has more complexity than a rigid body because the deformation is calculated inside as well as the outside the model. For this model, Gibson suggested the 3D ChainMail algorithm using volumetric data. However, in case of the deformable model with non-homogeneous materials, there were some discordances between visual and tactual sense information when calculating the force-feedback in real time. Therefore, we propose an algorithm for the Volume Haptic Rendering of non-homogeneous deformable object that reflects the force-feedback consistently in real time, depending on visual information (the amount of deformation), without any post-processing.

Traffic Lights Detection Based on Visual Attention and Spot-Lights Regions Detection (시각적 주의 및 Spot-Lights 영역 검출 기반의 교통신호등 검출 방안)

  • Kim, JongBae
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.6
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    • pp.132-142
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    • 2014
  • In this paper, we propose a traffic lights detection method using visual attention and spot-lights detection. To detect traffic lights in city streets at day and night time, the proposed method is used the structural form of a traffic lights such as colors, intensity, shape, textures. In general, traffic lights are installed at a position to increase the visibility of the drivers. The proposed method detects the candidate traffic lights regions using the top-down visual saliency model and spot-lights detect models. The visual saliency and spot-lights regions are positions of its difference from the neighboring locations in multiple features and multiple scales. For detecting traffic lights, by not using a color thresholding method, the proposed method can be applied to urban environments of variety changes in illumination and night times.

A Study of Individual Differences across Numerosity Sensitivity, Visual Working Memory and Visual Attention (수량민감도와 시각작업기억 및 시각적 주의 간 개인차 연구)

  • Kim, Giyeon;Cho, Soohyun;Hyun, Joo-Seok
    • Science of Emotion and Sensibility
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    • v.18 no.2
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    • pp.3-18
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    • 2015
  • Numerosity perception is considered as an innate ability of human being where its sensivitiy may widely vary across each individual person. The present study explored the relationship between visual working memory (VWM), visual search efficiency, and numerosity sensitivity. To accomplish this, we calculated each participant's K-value from change detection performance representing one's storage capacity in VWM, slopes of search RTs representing the search efficiency, and discrimination sensitivity for a quantity difference across two sets of dot arrays representing the numerosity sensitivity. The correlational analysis across the measurements revealed that participants with a high VWM capacity better discriminated the numerosity difference in the arrays when the spatial information in the two dot arrays was preserved. In contrast, the participants with high search efficiency discriminated better the difference in the arrays when the spatial information in the arrays was not preserved. The results indicate high VWM-capacity individuals were presumably able to use a strategy of storing the dot arrays by grouping them into a smaller pattern of dot arrays while high search-efficiency individuals were able to use a strategy of rapidly switching their focused attention across the dots in the arrays to count each individual dot. These in sum suggest that individual differences in numerosity sensitivity rely on one's working memory capacity as well as their efficient use of switching focused attention.