• 제목/요약/키워드: attentive object

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특징 지도를 이용한 중요 객체 추출 (Extraction of Attentive Objects Using Feature Maps)

  • 박기태;김종혁;문영식
    • 대한전자공학회논문지SP
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    • 제43권5호
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    • pp.12-21
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    • 2006
  • 본 논문에서는 컬러 영상에서 배경의 복잡도와 객체의 위치에 관계없이 영상 내에 존재하는 중요 객체를 자동으로 추출하는 방법을 제안한다. 제안하는 방법은 중요 객체를 추출하기 위해 에지(edge) 정보와 색상(color) 정보를 이용한 특징 지도를 사용한다. 또한, 효과적인 객체 추출을 위해서 참조 지도(reference map)를 제안한다. 참조 지도를 생성하기 위해서는 영상에서 사람의 시각에 두드러지게 구분되는 영역을 표현하는 특징 지도(feature map)를 먼저 생성한다. 그런 다음, 특징 지도들을 효과적으로 결합하여 배경의 영향을 최소화 하면서, 중요 객체가 존재할 확률이 높은 영역들을 포함하는 참조 지도를 생성한다. 특징 지도를 생성하기 위해서는 밝기 차 정보를 나타내는 에지와 YCbCr 컬러와 HSV 컬러 공간에서의 색상 성분을 사용하며, 특징 지도에 대한 생성 방법은 영상 내에서 밝기차이와 색상차이에 의해서 나타나는 경계 부분을 추출하는 방법을 사용한다. 최종적으로 중요 객체가 존재하는 영역을 나타내기 위해서 참조 지도와 특징 지도들을 결합한 결합 지도(combination map)를 생성한다. 결합 지도는 중요 객체의 외곽선 정보만을 표현하기 때문에, 객체 전체를 표현할 수 있는 객체 후보 영역을 추출하는데, 이를 위해서는 객체 후보 영역을 추출하기 위해서 convex hull 알고리즘을 사용한다. Convex hull 알고리즘에 의해서 추출된 영역은 여전히 배경 부분을 포함하고 있으므로, 영상 분할 방법을 적용하여 배경을 제거한 후 영상에서의 중요 객체를 추출한다. 제안한 알고리즘의 성능을 실험적으로 확인한 결과, 평균적으로 84.3%의 정확율과 81.3%의 재현율의 성능을 보였다.

유아의 물체영속성개념 발달에 관한 실험연구 (Development of the Concept of Object Permanence in Infancy)

  • 박경자
    • 아동학회지
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    • 제2권
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    • pp.1-16
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    • 1981
  • This study had two purposes. First, to examine the stages and developmental order of object permanence based on Piaget's theory. Second, to assess the effects of delay, attentiveness, and direction of gaze. Two experiments were conducted to examine the object permanence development in infants. The subjects for the 2 experiments were randomly drawn from a well-baby clinic. The subjects for Experiment 1 were 72 infants, 12 each in 6 age levels : 6, 9, 12, 15, 18, and 21 months old. Experiment 1 was designed to examine the stages and developmental order of object concept development, ana infants received 5 tasks as follows : (1) finding an object partially hidden under one box (2) finding an object completely hidden under one box (3) finding an object after successive visible displacements (4) finding an object after one invisible displacement (5) finding an object after successive invisible displacements. The subjects for Experiment 2 were 24 9-month-olds. Experiment 2 was designed to assess the effects of delay, attentiveness, and direction of gaze for Stage IV of object concept development. Subjects were equally assigned into one of two delay groups: 0-sec delay and 3-sec delay. Attentiveness was rated in terms of a three-point scale, and then divided into high and low attentive groups. Direction of gaze was judged into two directions. In two experiments, infants received three trials of task, and received a score of 0, 1, 2 for each trials. Data were analyzed by ANOVA, Tukey test, and t-test for task performance, and direction of gaze was analyzed by chi-square. The results obtained from two experiments were as follows : 1. In object permanence test, subjects obtained significantly higher scores with age, and 6, 9, 12, 18 months were classified into different developmental stages. 2. In object permanence development, subjects received significantly different scores with task and a developmental order of tasks was found. First of all, infants mastered finding an object partially hidden under one box, and then mastered finding an object completely hidden under one box. Contrary to Piagetian theory, in this study, the development of finding an object after successive visible displacements and finding an object after one invisible displacement were sometimes reversed. Finally, finding an object after successive invisible displacements was mastered, and the concept of object permanence was completed. 3. In Stage IV of object concept development, a 3-sec delay did not significantly affect the performance of tasks. The O-sec delay group didn't perform significantly better than the 3-sec delay group. 4. In Stage IV of object concept development, attentiveness of infants significantly affected the performance of task. So the highly attentive infants obtained better performance scores than the low attentive infants. 5. In Stage IV of object concept development, direction of gaze significantly affected the performance of task. That is, infants who gazed at the box which contained the object showed a higher rate of success than infants who gazed at the box which had already displaced the object.

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이동로봇의 물체인식을 위한 질의 기반 시각 집중 알고리즘 (Query-based Visual Attention Algorithm for Object Recognition of A Mobile Robot)

  • 류광근;이상훈;서일홍
    • 전자공학회논문지SC
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    • 제44권1호
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    • pp.50-58
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    • 2007
  • 본 논문에서는 로봇이 태스크와 관련된 부분에 시각 집중을 하도록 하기 위해서 기존의 상향식 주목 알고리즘을 확장한 질의 기반 시각 집중 알고리즘을 제안한다. 질의 기반 시각 집중 알고리즘은 로봇이 수행 할 태스크와 관련한 물체를 질의하면 그 물체의 속성을 분석하여 여러 종류의 도드라짐(Conspicuity) 영상 지도에 적용될 가중치 값을 작성한다. 그리고 가중치를 이용하여 도드라짐 영상 지도를을 합성한 Saliency 영상 지도를 작성하여 기존의 주목 알고리즘과 비교 평가를 수행하였다. 여기서는 일예로서 질의 물체의 속성을 색으로 사용하였다.

물체 인식을 위한 시각 주목 알고리즘 (Visual Attention Algorithm for Object Recognition)

  • 류광근;이상훈;서일홍
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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    • pp.306-308
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    • 2006
  • We propose an attention based object recognition system, to recognize object fast and robustly. For this we calculate visual stimulus degrees and make saliency maps. Through this map we find a strongly attentive part of image by stimulus degrees, where local features are extracted to recognize objects.

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엣지 디바이스에서 객체 탐지를 위한 그룹별 어탠션 기반 경량 디코더 연구 (A group-wise attention based decoder for lightweight salient object detection on edge-devices)

  • 티엔투고;엠디 딜로와르 호씬;허의남
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2023년도 추계학술발표대회
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    • pp.30-33
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    • 2023
  • The recent scholarly focus has been directed towards the expeditious and accurate detection of salient objects, a task that poses considerable challenges for resource-limited edge devices due to the high computational demands of existing models. To mitigate this issue, some contemporary research has favored inference speed at the expense of accuracy. In an effort to reconcile the intrinsic trade-off between accuracy and computational efficiency, we present novel model for salient object detection. Our model incorporate group-wise attentive module within the decoder of the encoder-decoder framework, with the aim of minimizing computational overhead while preserving detection accuracy. Additionally, the proposed architectural design employs attention mechanisms to generate boundary information and semantic features pertinent to the salient objects. Through various experimentation across five distinct datasets, we have empirically substantiated that our proposed models achieve performance metrics comparable to those of computationally intensive state-of-the-art models, yet with a marked reduction in computational complexity.

Dual Attention Based Image Pyramid Network for Object Detection

  • Dong, Xiang;Li, Feng;Bai, Huihui;Zhao, Yao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권12호
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    • pp.4439-4455
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    • 2021
  • Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.

자율주행 상황에서의 날씨 조건에 집중한 날씨 분류 및 영상 화질 개선 알고리듬 (Weather Classification and Image Restoration Algorithm Attentive to Weather Conditions in Autonomous Vehicles)

  • 김재훈;이정환;김상민;정제창
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송∙미디어공학회 2020년도 추계학술대회
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    • pp.60-63
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    • 2020
  • With the advent of deep learning, a lot of attempts have been made in computer vision to substitute deep learning models for conventional algorithms. Among them, image classification, object detection, and image restoration have received a lot of attention from researchers. However, most of the contributions were refined in one of the fields only. We propose a new paradigm of model structure. End-to-end model which we will introduce classifies noise of an image and restores accordingly. Through this, the model enhances universality and efficiency. Our proposed model is an 'One-For-All' model which classifies weather condition in an image and returns clean image accordingly. By separating weather conditions, restoration model became more compact as well as effective in reducing raindrops, snowflakes, or haze in an image which degrade the quality of the image.

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공간의 지각과 인지과정에 나타난 주시메커니즘 특성 연구 (A Study on the Characteristics of Observation seen in the Process of Perception and Recognition of Space)

  • 김종하
    • 한국실내디자인학회논문집
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    • 제22권6호
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    • pp.108-118
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    • 2013
  • This study has analyzed the process of space information perceived and recognized through the estimation of observation frequency and number according to the time range of observation data acquired from observation experiment with the object of hospital lobby. The followings are the results analyzed at this study. First, the continual observation of 3 and 6 times was attentive and conscious for probing to find an object rather than for acquiring exact information and that of 9 times could be regarded as the time for acquiring visual appreciation. However, the repetitive occurrence of high and low frequencies can be thought of repetitive acts for visual appreciation. Second, the continual observation of 3 and 6 times had the highest observation frequency of II, while that of 9 times had the highest observation frequency of III. In case of 3 and 6 times, the observation frequency had the tendency to become a little higher after being low since V, and in case of 9 times it had the repetition of becoming low and high and from IX it characteristically got higher. This feature can be thought to be the process that the subject repeats the fixation and movement of observation at a visual activity for perception and recognition. In the process of first observation, the observation frequency was the highest after 20 seconds or so, but since then, it gets lower and repeatedly gets higher and lower as time passes. After 90 seconds, the frequency showed the tendency of getting higher continuously. Third, the examination of changing features of frequency may show the characteristics of exploration for and attention to space but if the observation frequency is not associated with observation times for analysis there will a limitation that the features of observation frequency cannot be clarified. Accordingly, the simultaneous analysis of both is very effective for estimating the observation characteristics seen at the processes of perception and recognition. Fourth, the general analysis of the both revealed: with the progress of observation time the discontinuous space exploration decreased, and as the observation time got longer the fixed attention to a specific spot increased. Fifth, in order to estimate the observation characteristics by the change of time range the observation frequency and times by trend line was analyzed, which approach seems to be an appropriate technique that can comprehensively show the overall flow of time series data.

실제 과학수업에서 시선추적과 주의력 검사를 통한 초등학생들의 주의 특성 분석 (An Analysis of Elementary Students' Attention Characteristics through Attention Test and the Eye Tracking on Real Science Classes)

  • 신원섭;신동훈
    • 한국과학교육학회지
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    • 제36권4호
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    • pp.705-715
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    • 2016
  • 이 연구의 목적은 실제 과학수업에서 시선추적과 주의력 검사를 통해 초등학생들의 주의의 특성을 분석하는 것이다. 초등학생들의 주의 과정을 분석하기 위하여 SMI사의 ETG(eye tracker glasses) 이동형 시선추적기를 사용하였고, 샘플링 속도는 30Hz이다. 사전 주의력 검사의 연구대상은 초등학교 6학년 155명이었고, 시선추적의 연구 대상은 초등학교 6학년 남학생 6명이었다. 시선추적의 연구대상자는 모두 과거 안구병력이 없었으며, 안경을 쓰지 않았다. 안구운동 분석은 'BeGaze Mobile Video Analysis Package' 프로그램을 사용하였다. 연구결과는 다음과 같다. 첫째, 초등학생의 주의력 검사 결과, 선택적 주의와 자기통제는 .316으로 낮은 상관을 보였고, 선택적 주의와 지속적 주의는 .85로 높은 상관을 보였다. 둘째, 선택적 주의와 자기 통제의 상관관계를 기준으로 초등학생들의 주의 유형을 주의형(attentive type), 비주의형(inattentive type), 안이형(easygoing type), 경솔형(hasty type)으로 구분하였다. 셋째, 실제 과학수업에서 초등학생들의 안구운동분석을 통해 초등학생들의 주의는 상향식 주의처리, 하향식 주의처리, 디폴트 모드 네트워크로 구분할 수 있었다. 또한 실제 수업에서 초등학생들의 주의 전환은 다양한 원인으로 인해 빈번히 발생하였다. 초등학생들이 목표 지향적이고 지식에 의존하는 하향식 주의 처리를 못하는 원인은 초점주의 실패로 인한 목표 대상 지각의 실패, 목표 대상에 대한 관련지식의 부재, 관련지식에 대한 유추의 실패 등으로 나타났다. 주의력 검사와 안구운동분석을 종합하여 초등학생의 주의 처리과정을 도식하였다. 이 연구에서 밝힌 초등학생의 주의 특성과 주의 처리과정이 효과적인 교수전략, 교수학습 모형, 교수자료를 개발하는데 기초적인 자료로 활용될 것을 기대한다.