• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.117-122
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• 2023

Gaze estimation, which automatically recognizes where a user is currently staring, and object detection based on estimated gaze point, can be a more accurate and efficient way to understand human visual behavior. in this paper, we propose a method to detect the objects within the region of interest around the gaze point. Specifically, after estimating the 3D gaze point, a region of interest based on the estimated gaze point is created to ensure that object detection occurs only within the region of interest. In our experiments, we compared the performance of general object detection, and the proposed object detection based on region of interest, and found that the processing time per frame was 1.4ms and 1.1ms, respectively, indicating that the proposed method was faster in terms of processing speed.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Korean Ophthalmic Optics Society
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• v.16 no.4
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• pp.383-390
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• 2011

Purpose: The present study was conducted to investigate whether refractive powers of soft contact lenses were induced by the deposition of tear proteins when wearing soft contact lenses. Methods: The soft contact lenses (material: etafilcon A, hilafilcon A and comfilcon A) with refractive powers of -1.00 D, -3.00 D, -5.00 D and -7.00 D were incubated in artificial tear for 1 day, 3 days, 5 days, 7 days and 14 days, respectively. After incubation, their refractive powers were measured by wet cell method with an auto-lens meter and their protein deposited on the lenses was determined by the method of Lowry. Results: Among three types of soft contact lenses, the most protein deposition was detected in ionic etafilcon A lens material and significant change of its refractive power was manifested. In other words, refractive powers of etafilcon A lenses firstly decreased after 1 day incubation in artificial tear and then gradually increased with increasing incubation period again. The observed change in refractive powers of all diopters of etafilcon A material was beyond the scope of standard error and bigger in the lens with lower optical power. On the other hand, non-ionic hilafilcon A showed less protein deposition as much as about 20% in etafilacon A and statistically significant increase of refractive powers with increasing incubation period in artificial tear. The change in refractive power of hilafilcon A was also beyond the scope of the standard of error when incubating in artificial tear and greater in the lens with lower diopter. The least protein deposit was shown in silicone hydrogel lens material, comfilcon A as approximately 10% of it in etafilcon A, indicating less change in refractive power within the standard range of error. Conclusions: The large change of refractive powers that was beyond the scope of standard error by the deposition of tear proteins on soft contact lenses was differently detected depending on lens materials in the current study. Thus, the deposition of tear proteins induced by longer period of lens wearing may be one of the causes that induces blurred vision, suggesting that soft contact lens wearers with the amount of tear proteins may need to choose proper lens material.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.621-628
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• 2021

This paper proposes a method to calibrate a thermal camera with three different perspectives. In particular, the intrinsic parameters of the camera and re-projection errors were provided to quantify the accuracy of the calibration result. Three lenses of the camera capture the same image, but they are not overlapped, and the image resolution is worse than the one captured by the RGB camera. In computer vision, camera calibration is one of the most important and fundamental tasks to calculate the distance between camera (s) and a target object or the three-dimensional (3D) coordinates of a point in a 3D object. Once calibration is complete, the intrinsic and the extrinsic parameters of the camera(s) are provided. The intrinsic parameters are composed of the focal length, skewness factor, and principal points, and the extrinsic parameters are composed of the relative rotation and translation of the camera(s). This study estimated the intrinsic parameters of thermal cameras that have three lenses of different perspectives. In particular, image enhancement based on a deep learning algorithm was carried out to improve the quality of the calibration results. Experimental results are provided to substantiate the proposed method.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.425-435
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• 2016

In this paper, we propose a classification model by analyzing raw material images recorded using a color CCD camera to automatically classify good and defective agricultural products such as rice, coffee, and green tea, and raw materials. The current classifying agricultural products mainly depends on visual selection by skilled laborers. However, classification ability may drop owing to repeated labor for a long period of time. To resolve the problems of existing human dependant commercial products, we propose a vision based automatic raw material classification combining mean shift clustering and stepwise region merging algorithm. In this paper, the image is divided into N cluster regions by applying the mean-shift clustering algorithm to the foreground map image. Second, the representative regions among the N cluster regions are selected and stepwise region-merging method is applied to integrate similar cluster regions by comparing both color and positional proximity to neighboring regions. The merged raw material objects thereby are expressed in a 2D color distribution of RG, GB, and BR. Third, a threshold is used to detect good and defective products based on color distribution ellipse for merged material objects. From the results of carrying out an experiment with diverse raw material images using the proposed method, less artificial manipulation by the user is required compared to existing clustering and commercial methods, and classification accuracy on raw materials is improved.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.341-346
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• 2009

The motion data glove is a representative human-computer interaction tool that inputs human hand gestures to computers by measuring their motions. The motion data glove is essential equipment used for new computer technologiesincluding home automation, virtual reality, biometrics, motion capture. For its popular usage, this paper attempts to develop an inexpensive visual.type motion data glove that can be used without any special equipment. The proposed approach has the special feature; it can be developed as a low-cost one becauseof not using high-cost motion-sensing fibers that were used in the conventional approaches. That makes its easy production and popular use possible. This approach adopts a visual method that is obtained by improving conventional optic motion capture technology, instead of mechanical method using motion-sensing fibers. Compared to conventional visual methods, the proposed method has the following advantages and originalities Firstly, conventional visual methods use many cameras and equipments to reconstruct 3D pose with eliminating occlusions But the proposed method adopts a mono vision approachthat makes simple and low cost equipments possible. Secondly, conventional mono vision methods have difficulty in reconstructing 3D pose of occluded parts in images because they have weak points about occlusions. But the proposed approach can reconstruct occluded parts in images by using originally designed thin-bar-shaped optic indicators. Thirdly, many cases of conventional methods use nonlinear numerical computation image analysis algorithm, so they have inconvenience about their initialization and computation times. But the proposed method improves these inconveniences by using a closed-form image analysis algorithm that is obtained from original formulation. Fourthly, many cases of conventional closed-form algorithms use approximations in their formulations processes, so they have disadvantages of low accuracy and confined applications due to singularities. But the proposed method improves these disadvantages by original formulation techniques where a closed-form algorithm is derived by using exponential-form twist coordinates, instead of using approximations or local parameterizations such as Euler angels.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.367-376
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• 2015

This study is executed to investigate convergent factors related to depression among some college women of health affiliated educations. It surveyed 419 college women in Honam area during the period from March 9th to April 30th, 2015. The structured self-administered questionary was delivered and they were collected without respondents' personal information. The results of multiple regression analysis show the followings. The depression level of respondents turned out to be significantly higher in following groups: a group that experienced school bullying or violence, a group in which sleeping time is improper, a group in which subjective health status is bad, a group in which subjective happiness is lower, a group in which type A behavior pattern is higher, a group in which job seeking stress is higher, a group in which self esteem is lower, a group in which hopelessness is higher. Their explanatory power was 42.8%. The results indicate that the efforts to prevent bullying and violence experience, to get the proper amount of sleep, to be healthy, to increase subjective happiness and self esteem, to decrease type A behavior pattern, job seeking stress and hopelessness, are required to reduce the depression level of the college women of health affiliated educations.

• Korean Journal of Cognitive Science
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• v.10 no.3
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• pp.51-66
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• 1999

Selective attention induces perceptual distortions. ranging from repulsion of objects located near the attended area(Suzuki & Cavanagh. 1997) to magnification of the u unattended objects (Tsal & Shalev. 1996). Two hypothetical mechanisms have been p postulated: a shift of receptive fields' positions away from the locus of attention(receptive-field-recruitment hypothesis) or the enlargement of perceived space around the a attended location(space-enlargement hypothesis). The present study distinguished between these hypotheses by investigating the spatial and temporal properties of attention-induced d distortions. Perceptual judgements on vernier alignment. line tilt. line length were used to measure attention-induced changes in perception. Attention was induced exogenously(by blinking a specific set of dots around the test stimuli} or endogenously(by instructing the subject to selectively attend the dots). After inducing attention. the test stimuli were briefly flashed. A staircase method was used to measure the attentional effect. A vertical line was perceived as repelled from the locus of attention. and a line segment appeared longer when attention was given to its vicinity. The effects decreased as the distance between the locus of attention or the time between the onset of attention and the stimulus presentation increased. The results imply that the space-enlargement hypothesis provides a better explanation for the attention-induced changes in perception than the receptive-field-recruitment hypothesis.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.323-333
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• 2016

This study investigates convergent influence on job seeking stress and its association with self esteem, hopelessness, depression, locus of control and type A behavior pattern among some college women. The survey was administered to 531 college women in Jeonbuk area from March 28th to April 29th, 2016. The structured self-administered questionaries were used. The results of hierarchical multiple regression analysis show the following. The job seeking stress of respondents turned out to be significantly higher in following groups: a group in which self esteem is lower and groups in which hopelessness, depression, external locus of control and type A behavior pattern are higher. Their explanatory power was 43.2%. With the analysis of covariance structure, we could confirm relationship among the four factors such as self esteem, hopelessness, depression, locus of control, type A behavior pattern and job seeking stress. The results of the study indicate that the efforts, to increase self esteem, and to decrease hopelessness, depression, locus of control and type A behavior pattern, are required to reduce the job seeking stress of the college women. The results are expected to be useful for the development of program and policy to decrease the job seeking stress of the college women. In the following study, the analysis about additional factors of influence on job seeking stress will be needed.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.30-32
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• 2004

With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. The first establishes reference points in space, and the second uses a grid type frame and statistical method. But, the former has difficulty to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. It can easily estimate camera calibration parameters such as lens distortion, focal length, scale factor, pose, orientations, and distance. The advantage of this algorithm is that it can estimate the distance of the object. Also, the proposed camera calibration method is possible estimate distance in dynamic environment such as autonomous navigation. To validate proposed method, we set up the experiments with a frame on rotator at a distance of 1, 2, 3, 4[m] from camera and rotate the frame from -60 to 60 degrees. Both computer simulation and real data have been used to test the proposed method and very good results have been obtained. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. The average scale factor tends to fluctuate with small variation and makes distance error decrease. Compared with classical methods that use stereo camera or two or three orthogonal planes, the proposed method is easy to use and flexible. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use.