• The Research Journal of the Costume Culture
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• v.20 no.6
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• pp.912-922
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• 2012

With a long crotch length and much ease in the hip area, baggy pants are visually expressed in a variety of designs when compared with regular pants. The purpose of this study is to define the image differences of various baggy pants designs according to hip circumference and crotch length ease. To that end, this study deduced the visual image variable of experimental baggy pants and analyzed visual images according to changes in hip circumference and crotch length. Nine baggy pants with different levels of hip circumference and crotch length ease were produced as experimental pants. The image of each pair of experimental baggy pants was evaluated based on pictures taken of the pants worn by a woman in her 20s with a standard body figure. The image assessment team was composed of 105 clothing majors. The research results are as follows. Four visual image factors of experimental baggy pants were extracted: whole body compensation, lower body compensation, hip compensation, and waist compensation. Among the 4 factors, the whole body compensation factor was shown as the most representative factor. The body compensation image was higher with less hip circumference ease in the experimental baggy pants, and more hip circumference ease created the optical illusion of a larger body figure, presenting a significant difference between waist circumference and hip circumference. The lower body compensation factor, hip compensation factor, and waist compensation factor all showed a significant influence on changes in hip circumference ease. This result shows that changes in hip circumference ease exerted more influence on the body compensation image than did changes in crotch length ease. The results of this study provide basic data for predicting visual images according to differences in the level of ease in baggy pants, helping people select clothing suitable to their preferences and body shapes.

• Fashion & Textile Research Journal
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• v.15 no.4
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• pp.504-513
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• 2013

This study evaluates the difference of visual effect according to pant style and geometric pattern. The researcher made 28 stimuli-combination of four pant Stiles (classic, baggy, skinny, and bell-bottom) and seven geometric pattern (large vertical stripe, small vertical stripe, large horizontal stripe, small horizontal stripe, large check, small check, and hound's tooth check). The test involved 96 female college students. The stimuli were made with the i-Designer computer program. The panels tested the computer screen images of all manikins wearing pants. A 7-point scale was used to evaluate each image. For the data analysis, ANOVA and Duncan-test were applied along with an SPSS program. The results of this study are as follows. Three factors (lower-body compensation, abdomen highlight, and length compensation) influenced the visual effect pant styles and geometric patterns. The skinny style and large vertical stripe evaluated positively in elongated height and leg length and a slimmer overall body. It was shown that the vertical stripe pattern was evaluated as more positive than the horizontal stripe pattern in the visual effect; particularly, the results showed distinct aspects in the classic pants style. The mutual influence of the visual effect (according to pants style and geometric pattern) were indicated as two factors of lower-body compensation and length compensation. A more positive visual effects resulted in a higher mutual influence on pant style and geometric pattern.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5998-6016
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• 2017

In thin-film transistor liquid-crystal displays (TFT-LCDs), which are most commonly used in mobile devices, the backlight accounts for about 70% of the power consumption. Therefore, most low-power-related studies focus on realizing power savings through backlight dimming. Image compensation is performed to mitigate the visual distortion caused by the backlight dimming. Therefore, popular techniques include pixel compensation for brightness recovery and contrast enhancement, such as histogram equalization. However, existing pixel compensation techniques often have limitations with respect to blur owing to the pixel saturation phenomenon, or because contrast enhancement cannot adequately satisfy the human visual system (HVS). To overcome these, in this study, we propose a novel dimming technique to achieve both power saving and HVS-awareness by combining the pixel compensation and histogram specifications, which convert the original cumulative density function (CDF) by designing and using the desired CDF of an image. Because the process of obtaining the desired CDF is customized to consider image characteristics, histogram specification is found to achieve better HVS-awareness than histogram equalization. For the experiments, we employ the LIVE image database, and we use the structural similarity (SSIM) index to measure the degree of visual satisfaction. The experimental results show that the proposed technique achieves up to 15.9% increase in the SSIM index compared with existing dimming techniques that use pixel compensation and histogram equalization in the case of the same low-power ratio. Further, the results indicate that it achieves improved HVS-awareness and increased power saving concurrently compared with previous techniques.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.51-60
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• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.694-699
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• 2009

This paper presents the implementation of the real-time object tracking control of the ROBOKER head. The visual servoing technique is used to track the moving object, but suffers from ill-estimated Jacobian of the virtual link design. To improve the tracking performance, the RBF(Radial Basis Function) network is used to compensate for uncertainties in the kinematics of the robot head in on-line fashion. The reference compensation technique is employed as a neural network control scheme. Performances of three schemes, the kinematic based scheme, the Jacobian based scheme, and the neural network compensation scheme are verified by experimental studies. The neural compensation scheme performs best.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.248-254
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• 2006

It is necessary to improve the exactness and adaptation of the working environment for the intelligent robot system. The vision sensor have been studied for a long time at this points. However, it has many processes and difficulties for the real usages. This paper proposes a visual servoing in the virtual environment to support OLP(Off-Line-Programming) path compensation and supplement the problem of complexity of the old kinematical calibration. Initial robot path could be compensated by pixel differences between real and virtual image. This method removes the varies calibrations and 3D reconstruction process in real working space. To show the validity of the proposed approach, virtual space servoing with stereo camera is carried out with WTK and openGL library for a KUKA-6R manipulator and updated real robot path.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.95-102
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• 2004

It is necessary to improve the exactness and adaptation of the working environment in the intelligent robot system. The vision sensor have been studied for this reason fur a long time. However, it is very difficult to perform the camera and robot calibrations because the three dimensional reconstruction and many processes are required for the real usages. This paper suggests the image based visual servoing to solve the problem of old calibration technique and supports OLP(Off-Line-Programming) path compensation. Virtual camera can be modeled from the real factors and virtual images obtained from virtual camera gives more easy perception process. Also, Initial path generated from OLP could be compensated by the pixel level acquired from the real and virtual, respectively. Consequently, the proposed visually assisted OLP teaching remove the calibration and reconstruction process in real working space. With a virtual simulation, the better performance is observed and the robot path error is calibrated by the image differences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• The Research Journal of the Costume Culture
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• v.20 no.3
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• pp.309-318
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• 2012

This study aimed to find the components of visual image by researching main image-related adjectives applied to high-waist skirts. In addition, it compared and analyzed the differences and mutual influences of visual images according to variations in the waistline and skirt length of high-waist skirts. The researchers made nine high-waist skirts-combinations of three different levels of waistlines and skirt lengths. The test involved 121 people who hold degrees in the field of Clothing and Textiles. The panels tested actual images of all models wearing the high-waist skirts shown on a computer screen. The results of the study are as follows.: Four factors affected the visual image as waist-height and skirt-length changed: attractiveness, upper-body compensation, length compensation, and hips compensation. Among these factors, attractiveness was estimated as the most important factor. The torso and the hip were highlighted as the waistline increased from 3cm to 11cm, due to the optical illusion of a tighter skirt wrapping the bust, waist, and hips. As the waistline increased, the stature and leg length increased, possibly revising the overall appearance. For the skirt length, a length measuring 20cm above the knees, proved to be most attractive. This resulted in elongated height and leg length, and a slimmer overall look.