• Journal of Korea Multimedia Society
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• v.21 no.7
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• pp.755-763
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• 2018

In this paper, for recognize a night pedestrian from an infrared video, a new method differentiated from the existing feature vector is proposed and experimented. The new approach focuses on the shape feature vector of the structure and shape of the pedestrian image divided by the human body seven split ratio. The pedestrian images are divided into 7 square blocks from the still image of the preprocessing process. And to reduce the dimension, the square block is converted into a mosaic block. The scalar and direction of the shape feature vector is calculated by the brightness and position of the element in the mosaic. For practicality of infrared video system, the proposed method simplifies the data to be processed by reducing the amount of data in the preprocessing in order to continuously batch process the entire system in real time. Through the experiments, we verified the validity of the proposed shape feature vector. In comparison to the existing method, we propose a new shape feature vector generation method as the feature vector for night pedestrian recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4395-4412
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• 2020

The multisource image fusion has become an active topic in the last few years owing to its higher segmentation rate. To enhance the accuracy of multimodal pig-body feature segmentation, a multisource image fusion method was employed. Nevertheless, the conventional multisource image fusion methods can not extract superior contrast and abundant details of fused image. To superior segment shape feature and detect temperature feature, a new multisource image fusion method was presented and entitled as NSST-GF-IPCNN. Firstly, the multisource images were resolved into a range of multiscale and multidirectional subbands by Nonsubsampled Shearlet Transform (NSST). Then, to superior describe fine-scale texture and edge information, even-symmetrical Gabor filter and Improved Pulse Coupled Neural Network (IPCNN) were used to fuse low and high-frequency subbands, respectively. Next, the fused coefficients were reconstructed into a fusion image using inverse NSST. Finally, the shape feature was extracted using automatic threshold algorithm and optimized using morphological operation. Nevertheless, the highest temperature of pig-body was gained in view of segmentation results. Experiments revealed that the presented fusion algorithm was able to realize 2.102-4.066% higher average accuracy rate than the traditional algorithms and also enhanced efficiency.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.65-76
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• 2003

The analysis of cow body parameters is important to provide some useful information fur cow management and cow evaluation. Present methods give many stresses to cows because they are invasive and constrain cow postures during measurement of body parameters. This study was conducted to develop the stereo vision system fur non-invasive analysis of cow body features. Body feature parameters of 16 heads at two farms(A, B) were measured using scales and nineteen stereo images of them with walking postures were captured under outdoor illumination. In this study, the camera calibration and inverse perspective transformation technique was established fer the stereo vision system. Two calibration results were presented for farm A and fm B, respectively because setup distances from camera to cow were 510 cm at farm A and 630cm at farm B. Calibration error values fer the stereo vision system were within 2 cm for farm A and less than 4.9 cm for farm B. Eleven feature points of cow body were extracted on stereo images interactively and five assistant points were determined by computer program. 3D world coordinates for these 15 points were calculated by computer program and also used for calculation of cow body parameters such as withers height. pelvic arch height. body length. slope body length. chest depth and chest width. Measured errors for body parameters were less than 10% for most cows. For a few cow. measured errors for slope body length and chest width were more than 10% due to searching errors fer their feature points at inside-body positions. Equation for chest girth estimated by chest depth and chest width was presented. Maximum of estimated error fur chest girth was within 10% of real values and mean value of estimated error was 8.2cm. The analysis of cow body parameters using stereo vision system were successful although body shape on the binocular stereo image was distorted due to cow movements.

• Journal of Sasang Constitutional Medicine
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• v.20 no.1
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• pp.42-47
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• 2008

1. Objectives The Body Shape and Feature is one of the important standard for classification of Sasang Constitutions. In order to evaluate one's Body Shape and Feature objectively we have been developing the Body Measuring Machine. Now we develop the 3D Automatic Body Measuring Machine(3D-ABMM). So we make an analysis of the 3D-ABMM's Accuracy. 2. Methods By using the 3D-ABMM and Vivid 9i(3D laser scanner, Konica Minolta) we have a surface scan of the three objects which are the upper body of the female and male Manikin and a male model. We overlap each scan data using the RapidForm2006 (3D scan data solution, INUS Technology) and calculate the average distance and standard deviation between the same point of each scan data. 3. Results and Conclusions In the female Manikin, the average distance is 0.84mm and the standard deviation is 1.16mm and the maximum distance is 10.68mm. In the male Manikin, the average distance is 1.12mm and the standard deviation is 1.19mm and the maximum distance is 12.00mm. In the male model, the average distance is 3.26mm and the standard deviation is 2.59mm and the maximum distance is 12.75mm. From the results, 3D-ABMM has good accuracy for scanning body and will be a usable hardware of the 3D Automatic Body Analysis Machine.

• Fashion & Textile Research Journal
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• v.12 no.5
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• pp.582-590
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• 2010

Garment design needs an iterative manipulation of 2D patterns to generate a final sloper. Traditionally there have been two kinds of design methodologies such as the flat pattern method and the pattern draping method. But today, it is possible to combine the advantages from the two methods due to the realistic cloth simulation techniques. We devised a new garment design system which starts from 3D initial drape simulation result and then modifies the garment by editing the 2D flat patterns synchronously. With this interactive methodology using real-time pattern deformation technique, the designer can freely change a pattern shape by watching its 3D outlook in real-time. Also the final garment data were given relative coordinates with respect to the human anthropometric feature points detected by an automatic body feature detection algorithm. Using the relative human body coordinate system, the final garments can be re-used to an arbitrary body data without repositioning in the drape simulation. A female shirt was used for an example and a 3D body scan data was used for an illustration of the feature point detection algorithm.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.996-1008
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• 2009

This paper proposes a novel approach for the model-based pose matching of a human body using Active Shape Models. To improve the processing time of model creation and registration, we use a skeleton-type model instead of the conventional silhouette-based models. The skeleton model defines feature information that is used to match the human pose. Images used to make the model are for 600 human bodies, and the model has 17 landmarks which indicate the body junction and key features of a human pose. When applying primary Active Shape Models to the skeleton-type model in the matching process, a problem may occur in the proximal joints of the arm and leg due to the color variations on a human body and the insufficient information for the fore-rear directions of profile normals. This problem is solved by using the background subtraction information of a body region in the input image and adding a 4-directions feature of the profile normal in the proximal parts of the arm and leg. In the matching process, the maximum iteration is less than 30 times. As a result, the execution time is quite fast, and was observed to be less than 0.03 sec in an experiment.

• The Research Journal of the Costume Culture
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• v.19 no.3
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• pp.449-459
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• 2011

The purpose of this study is investigate the feature of the body shape of obese males and to propose a new apparel sizing system considering the body size of obese men through an the analysis of the body measurement of obese men in their twenties as reported in the 'Fifth Korean National Physical Standard Reports'. For this study, a new apparel sizing system for casual wear was proposed for obese men in their twenties after a body measurement of 159 obese men in their 20s with a BMI of 25 and over as reported in the 'Fifth Korean National Physical Standard Reports' conducted by SIZEKOREA. This study sought to investigate the features of obese men's bodies by comparing the body shape between obese men and ordinary men. The result of shows that width, depth and circumference items influencing the width size when producing clothes are larger in the case of an obese body shape than an ordinary body shape, and that the stature, total length, arm length and outside leg length influencing the length size are similar between an obese body shape and an ordinary body shape. Therefore, it was confirmed that an apparel sizing system specializing in clothes for obese customers is required. As a result of this study of the features of body shape, the control dimensions for such an apparel sizing system were determined to be the stature and chest circumference of upper garments and the stature and waist circumference(omphalion) for lower garments. The interval between the sizes was 5cm for the stature and was irregular for the chest and waste circumference. Consequently, 8 sizes were proposed for upper garments and 9 sizes were proposed for lower garments.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.181-186
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• 2014

The paper proposes a new method of segmentation-based feature extraction to improve performance in pedestrian upper-body detection. General pedestrian detectors that use local features are often plagued by false positives due to the locality. Color information of multi parts of the upper body is utilized in figure-ground segmentation scheme to extract an salient, "global" shape feature capable of reducing the false positives. The performance of the multi-part color segmentation-based feature is evaluated by changing color spaces and the parameters of color histogram. The experimental result from an upper-body dataset shows that the proposed feature is effective in reducing the false positives of local feature-based detectors.

• Fashion & Textile Research Journal
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• v.11 no.5
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• pp.788-798
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• 2009

This study aims to develop a highly reproducible, optimal frame design algorithm using variations in the curvature of armscye circumference, which will provide the basics for remodeling the 3D human body shape with the concept of reverse design used to develop total contents for the apparel industry. 1. The results of the experiment proved that ratio value was significantly efficient than absolute value of curvature variation to extract feature points in the armscye circumference 2. For the shoulder(1st and 2nd quadrant) and front armhole(3rd quadrant) parts of the armscye circumference, frame remodeling with the positive point of inflection led to the completion of a highly reproducible frame. 3. Similarly, even for the rear armhole part(4th quadrant) in the armscye circumference, it was found that frame remodeling using the positive maximum point of inflection resulted in highly reproducible body shape with the maximum point of inflection situated within the range of split angles $305^{\circ}{\sim}330^{\circ}$, while frame remodeling using simultaneously the two largest points of inflection including maximum point of inflection led to highly reproducible body shape with the maximum point of inflection out of the range $305^{\circ}{\sim}330^{\circ}$. 4. Based upon the optimal frame design algorithm developed in this study, section-specific feature points in the armscye circumference were extracted depending on the rate of curvature variation and remodeling with spline curves was conducted. The results indicate a remarkably high reproducibility(98.6%) and suggest that the algorithm developed in this study is suitable for human body modeling.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.117-127
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• 2019

The purpose of this study was to analyze the direct measurement data of 40-59 year old middle-aged men from Size Korea's 7th anthropometric survey, and to identify the body shape characteristics and to type the body shape of middle-aged men. Through this, this study aimed to provide basic data necessary for the clothing patterns of middle-aged men with excellent fit. The data was SPSS Ver. 24.0 program analysis. Factors extracted six including body horizontal, vertical, shoulder, waist front length, leg thickness, and shoulder deflections. The body shape of middle-aged men was classified into three types. Type 1 had a thin body circumference, a narrow width, a low height, a short waist front length, and a thin ankle and calf. Type 2 had a high body height, a long waist front length, a normal circumference and width, a thick ankle, a calf, and a sagging shoulder. Type 3 had a large body circumference, a wide body, a wide shoulder, and a long waist front length. A prominent feature of the changes in body shape of middle-aged men is the increase in the circumference and thickness items due to abdominal protrusion and fat accumulation. Therefore, pattern design according to these physical characteristics is considered to be necessary.