• The Journal of Korean Physical Therapy
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• v.32 no.5
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• pp.283-289
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• 2020

Objective: The purpose of this study was to determine the force of lower extremities, the change in walking ability on the ground by applying a walking training program based on perceptual learning to improve gait capacity of chronic stroke patients. Method: This study included Twenty-four patients with chronic stroke. Using a perceptual-based gait training, the experimental group trained twice a day for 30 minutes each time, 5 times a week, for a total of 8 weeks. The control group underwent ground gait training that excluded the element of a perceptual training for 30 minutes, 5 times a week for 8 weeks. Results: In the two groups, the maximum forefoot pressure after intervention was significantly different in both the LEPGT and GGT (p<0.05). The maximum midfoot pressure was significantly different in LEPGT (p<0.05). There was a significant difference in the maximum heel pressure after intervention between the two groups (p<0.05). As a result of comparing the change in step length and stride length after intervention in the two groups, there was a significant difference between the two groups (p<0.05). Conclusion: Both gait training programs was found that gait training based on perceptual learning and ground gait training were the training for improving the functional gait of stroke patient. Perceptual learning gait training utilizing intensive perceptual awareness was the training for improving gait capacity within the period than ground gait training.

• Speech Sciences
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• v.13 no.3
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• pp.197-206
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• 2006

Perceptual judgement method is frequently used in evaluating dysarthric speech. Although most of speech pathologists and researchers focus on the 38 perceptual features provided by Darley, Aronson & Brown(1969) during evaluation, there are additional characteristics that may be useful to describe dysarthria in literature. We reviewed previous dysarthria literature and selected 46 perceptual characteristics that could be examined at various subsystems of speech production. We also provided explanations and rationale for the rating method for each of the perceptual characteristics. This attempt might aid to offer a basic ground for developing a diagnostic tool of dysarthria.

• The Journal of Korean Physical Therapy
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• v.15 no.3
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• pp.265-276
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• 2003

This study was to investigate the dffects of a color reversal visual perceptual training program on spastic cerebral palsied children's figure-ground discrimination disabilities and to investigate the difference between the control group and experimental group. Subjects of the study were composed of children with spastic cerebral palsy whose age varied from five to seven years old, whose I.Q. was over 70 and whose P.Q. was over 70. Implication of this study can be summarized as follows; First, Perceptual training and speech training programs should be emphasized to improve the preparative ability of spastic cerebral palsied children. Problems of perception cerebral palsied children are concerned with figure-ground discrimination disability. Second, Though it was demonstrated that color reversal visual perceptual training program can be effective through the prestudies and this study, more researches should be made to apply this kind of theory in real education environments. More interest in different color forms for training of cerebral palsied children should be taken. Third, Reprecations of the study should be considered with modified group identities(age, I.Q., P.Q.).

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.131-143
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• 2014

We propose a no-reference perceptual fog density and visibility prediction model in a single foggy scene based on natural scene statistics (NSS) and perceptual "fog aware" statistical features. Unlike previous studies, the proposed model predicts fog density without multiple foggy images, without salient objects in a scene including lane markings or traffic signs, without supplementary geographical information using an onboard camera, and without training on human-rated judgments. The proposed fog density and visibility predictor makes use of only measurable deviations from statistical regularities observed in natural foggy and fog-free images. Perceptual "fog aware" statistical features are derived from a corpus of natural foggy and fog-free images by using a spatial NSS model and observed fog characteristics including low contrast, faint color, and shifted luminance. The proposed model not only predicts perceptual fog density for the entire image but also provides local fog density for each patch size. To evaluate the performance of the proposed model against human judgments regarding fog visibility, we executed a human subjective study using a variety of 100 foggy images. Results show that the predicted fog density of the model correlates well with human judgments. The proposed model is a new fog density assessment work based on human visual perceptions. We hope that the proposed model will provide fertile ground for future research not only to enhance the visibility of foggy scenes but also to accurately evaluate the performance of defog algorithms.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.810-820
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• 2014

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance are reported. In near field, several hits per an object are generated after signal processing of Radar data. Hence, clustering is an essential technique to estimate their shapes and positions precisely. This paper proposes a method of grouping hits in range-doppler domains into clusters which represent each object, according to the pre-defined rules. The rules are based on the perceptual cues to separate hits by object. The morphological connectedness between hits and the characteristics of SNR distribution of hits are adopted as the perceptual cues for clustering. In various simulations for the performance assessment, the proposed method yielded more effective performance than other techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2547-2567
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• 2021

It has been widely acknowledged that occlusion impairments adversely distress many face recognition algorithms' performance. Therefore, it is crucial to solving the problem of face image occlusion in face recognition. To solve the image occlusion problem in face recognition, this paper aims to automatically de-occlude the human face majority or discriminative regions to improve face recognition performance. To achieve this, we decompose the generative process into two key stages and employ a separate generative adversarial network (GAN)-based network in both stages. The first stage generates an initial coarse face image without an occlusion mask. The second stage refines the result from the first stage by forcing it closer to real face images or ground truth. To increase the performance and minimize the artifacts in the generated result, a new refine loss (e.g., reconstruction loss, perceptual loss, and adversarial loss) is used to determine all differences between the generated de-occluded face image and ground truth. Furthermore, we build occluded face images and corresponding occlusion-free face images dataset. We trained our model on this new dataset and later tested it on real-world face images. The experiment results (qualitative and quantitative) and the comparative study confirm the robustness and effectiveness of the proposed work in removing challenging occlusion masks with various structures, sizes, shapes, types, and positions.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.145-147
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• 2014

공동주의는 사회적 개체간의 지각적 경험을 공유하는 상호작용과정으로, 최근 인간-로봇 상호작용연구와 관련해서 로봇 공학자의 관심이 커지고 있다. 발달심리학에 기초한 기존의 developmental robotics의 접근과는 달리, 본 연구에서는 사전단서 패러다임을 이용해서 목표물, 단서, 주의반응 간의 삼자관계를 수학적으로 개념화하였다. 간단한 목표물 탐사과제를 통해서 계산모형의 수행을 검증하였다. 연구결과에서는 컴퓨터 시스템의 시각적 주의 모형이 사용자가 지시하는 단서(손가락 지시)의해 목표물(이온음료)을 주의를 할당하는 것을 보였다. 본 연구는 심리학에서 연구된 사전단서 패러다임을 인간-로봇 상호작용에 적용될 수 있음을 보여준다.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.265-274
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• 2006

Extracting ground points is the kernel of DTM generation being considered as one of the most popular LIDAR applications. The previous extraction approaches can be mostly characterized as a point based approach, which sequentially examines every individual point to determine whether it is measured from ground surfaces. The number of examinations to be performed is then equivalent to the number of points. Particularly in a large set, the heavy computational requirement associated with the examinations is obviously an obstacle to employing more sophisticated criteria for the examination. To reduce the number of entities to be examined and produce more robust results, we developed an approach based on features rather than points, where a feature indicates an entity constructed by grouping some points. In the proposed approach, we first generate a set of features by organizing points into surface patches and grouping the patches into surface clusters. Among these features, we then attempt to identify the ground features with the criteria based on the attributes of the features. The points grouped into these identified features are labeled ground points, being used for DTM generation afterward. The Proposed approach was applied to many real airborne LIDAR data sets. The analysis on the results strongly supports the prominent performance of the proposed approach in terms of not only the computational requirement but also the quality of the DTM.

• ETRI Journal
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• v.41 no.6
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• pp.797-810
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• 2019

Image saliency detection is the basis of perceptual image processing, which is significant to subsequent image processing methods. Most saliency detection methods can detect only a single object with a high-contrast background, but they have no effect on the extraction of a salient object from images with complex low-contrast backgrounds. With the prior knowledge, this paper proposes a method for detecting salient objects by combining the boundary contrast map and the geodesics-like maps. This method can highlight the foreground uniformly and extract the salient objects efficiently in images with low-contrast backgrounds. The classical receiver operating characteristics (ROC) curve, which compares the salient map with the ground truth map, does not reflect the human perception. An ROC curve with distance (distance receiver operating characteristic, DROC) is proposed in this paper, which takes the ROC curve closer to the human subjective perception. Experiments on three benchmark datasets and three low-contrast image datasets, with four evaluation methods including DROC, show that on comparing the eight state-of-the-art approaches, the proposed approach performs well.

• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.45-52
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• 2023

Previous studies have established a role for cognitive differences in explaining variability in speech processing across individuals. In the case of perceptual cue weighting in the context of a sound change, studies have produced conflicting results regarding the relationship between executive function and the use of redundant cues. The current study aimed to explore this relationship in acoustic cue weighting during speech production. Forty-one Korean-speaking children read a list of stop-initial words and completed two tests that assess executive function, i.e., Dimensional Change Card Sorting (DCCS) and digit n-back. Voice onset time (VOT) and fundamental frequency (F0) were measured in each word, and analyses were carried out to determine the extent to which children's executive function predicted their use of both informative and less informative cues to the three pairs comprising the Korean three-way stop laryngeal contrast. No evidence was found for a relationship between cognitive ability and acoustic cue weighting in production, which is at odds with previous, albeit conflicting, results for speech perception. While this result may be due to the lack of task demands in the production task used here, it nevertheless expands the empirical ground upon which future work in this area may proceed.