• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.12-21
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• 2006

In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.

• Korean Journal of Child Studies
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• v.2
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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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.50-58
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• 2007

In this paper, we propose a query-based visual attention algorithm for effective object finding of a vision-based mobile robot. This algorithm is developed by extending conventional bottom-up visual attention algorithms. In our proposed algorithm various conspicuity maps are merged to make a saliency map, where weighting values are determined by query-dependent object properties. The saliency map is then used to find possible attentive location of queried object. To show the validities of our proposed algorithm, several objects are employed to compare performances of our proposed algorithm with those of conventional bottom-up approaches. Here, as one of exemplar query-dependent object property, color property is used.

• Proceedings of the KIEE Conference
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• 2006.04a
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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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.

• Korean Institute of Interior Design Journal
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• v.22 no.6
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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.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.705-715
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• 2016

The purpose of this research is to analyze elementary students' attention characteristics through attention test and eye tracking on real science classes. The SMI's ETG(eye tracker glasses) mobile eye tracker was used to analyze the attention process of elementary students'. The sampling rate of the ETG is 30Hz. The participants of attention test were elementary 155 6th-grade elementary students and the participants for the eye-tracker were six 6th-grade male students. The eye movements were analyzed using the 'BeGaze Mobile Video Analysis Package' program. The results of this research are as follows. First, the attention test results of elementary students showed high correlation between selective attention and sustained attention (.85) and low correlation between selective attention and self-regulation (.32). Second, the attention types of elementary students were divided into four; attention, inattention, easygoing and hasty. Third, elementary students' attention were divided into top-down, bottom-up, default mode network through analysis of elementary students′ eye-movements during real science classes. Also their attention shift occurred frequently due to various reasons in real class situation. There were three reasons that made elementary students fail to handle knowledge-dependent top-down attention; 1) the cognitive failure of target caused by failing to focus attention, 2) the absence of prior knowledge on target object, 3) the analogical failure of prior knowledge. Finally, elementary students' attention process were schematized based on the analysis of students' eye movements and attention test. This research is expected to be utilized as basic data for developing effective teaching strategies, teaching-learning models and instructional materials.