• Title, Summary, Keyword: Body Segmentation

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Active Contours Level Set Based Still Human Body Segmentation from Depth Images For Video-based Activity Recognition

  • Siddiqi, Muhammad Hameed;Khan, Adil Mehmood;Lee, Seok-Won
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.11
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    • pp.2839-2852
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    • 2013
  • Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

Body Segmentation using Gradient Background and Intra-Frame Collision Responses for Markerless Camera-Based Games

  • Kim, Jun-Geon;Lee, Daeho
    • Journal of Electrical Engineering and Technology
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    • v.11 no.1
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    • pp.234-240
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    • 2016
  • We propose a novel framework for markerless camera-based games. By using a visual camera, our method may yield robust human body segmentation with high performance comparable to the segmentation using depth cameras. The edges of human bodies are detected by subtracting gradient backgrounds, and human body regions are segmented by the operations based on mathematical morphology. Collisions between detected regions and virtual objects are determined by finding the colliding time using intra-frame positions of virtual objects. Experimental results show that the proposed method may produce robust segmentation of human bodies, thereby and the collision responses are more accurate than previous methods. Therefore, the proposed framework can be widely used in camera-based games requiring high performance.

Minimization of Support Structure Using Cone-Shaped Body Segmentation in Fused Deposition Modeling Type Small Size Human Manikin 3D Printing (원뿔형 인체분할을 이용한 용융 적층 방식 소형 인체 마네킨 3D 프린팅의 지지 구조 최소화)

  • Kim, Sungmin;Sul, In Hwan
    • Textile Science and Engineering
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    • v.55 no.3
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    • pp.194-201
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    • 2018
  • 3D printing was adopted to create a miniature human manikin. One of the disadvantages of 3D printing, especially fused deposition modeling type, is the need for a support structure for overhangs. The support structure can be waste of raw filament in a way, and also harms the surface smoothness of the final printed product. To minimize the amount of support structure, human body parts were dissected into cone-shaped segments by automatically finding bone and surface feature points. A commercial 3D printer was used and the printed manikins with and without body segmentation technique were compared quantitatively. Our cone-shaped segmentation-based printing scheme showed dramatically less amount of support structure and more smooth surfaces on most segments, except for non-cube shapes such as the head, hands, and feet.

A Study of Human Body Section Curve Modeling by Using Least Square NURBS Approximation Method (최소자승 NURBS 근사법을 이용한 인체 단면곡선 생성)

  • Han Sung Soo;Bae Han Jo;Park Jung Whan;Kwon Oh Hyun
    • Textile Science and Engineering
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    • v.42 no.5
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    • pp.323-328
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    • 2005
  • The paper proposes a method of constructing the three-dimensional CAD model from digitized cloud-of­points data of the human body, thereby automatically extracting several featured dimensions. The main steps are; segmentation, sectioning, fairing and surface approximation. In segmentation process the input three-dimensional set of points are grouped into each functional part of the human body by searching the boundary points when being viewed from a certain direction. The next step slices the grouped points to obtain section curves which will be faired (smoothed) by the difference-fairing method. Each faired section curve (a set of points) is approximated to the NURBS form by use of well known method, from which we can construct a NURBS surface. The parametric surfaces for functional parts of a human body are interrogated to extract several featured dimensions of a human body.

Exploiting Color Segmentation in Pedestrian Upper-body Detection (보행자 상반신 검출에서의 컬러 세그먼테이션 활용)

  • Park, Lae-Jeong
    • 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.

The Grid Pattern Segmentation Using Hybrid Method (하이브리드 방법을 이용한 격자 패턴의 세그먼테이션)

  • 이경우;조성종;주기세
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.1
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    • pp.179-184
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    • 2004
  • This paper presents an image segmentation algorithm to obtain the 3D body shape data that the grid pattern and the body contour lute in the background image are extracted using the new proposed hybrid method. The body contour line is extracted based on maximum biased anisotropic recognition(MaxBAR) algorithm which recognizes the most strong and robust edges in the image since the normal derivative at the edges is large, while the tangential derivatives can be small. The grid patterns within body contour lines are extracted by grid pattern detection (GPD). The body contour lilies and the grid patterns are combined. The consecutive run test based on heuristic method is used to link the disconnected line and reduce noise line. This proposed segmentation method is more effective than the conventional method which uses a gradient and a laplacian operator, verified with application two conventional method.

Robust 2D human upper-body pose estimation with fully convolutional network

  • Lee, Seunghee;Koo, Jungmo;Kim, Jinki;Myung, Hyun
    • Advances in robotics research
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    • v.2 no.2
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    • pp.129-140
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    • 2018
  • With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

Tongue Image Segmentation via Thresholding and Gray Projection

  • Liu, Weixia;Hu, Jinmei;Li, Zuoyong;Zhang, Zuchang;Ma, Zhongli;Zhang, Daoqiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.945-961
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    • 2019
  • Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.

Segmentation Using Curvature Information of 3D Body Surface for Tight-fit Pattern Making (상반신 밀착패턴 제작을 위한 3차원 인체 표면 곡률기준 분할)

  • Park, Hye-Jun;Hong, Kyung-Hi;Cho, Young-Sook
    • Journal of the Korean Society of Clothing and Textiles
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    • v.33 no.1
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    • pp.68-79
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    • 2009
  • It is inevitable to have cutting line to get the 2D pattern from 3D body surface. In this paper the efficiency of curvature plot as a cutting line in the process of flattening 3D surface was investigated. As reference, basic clothing construction line was adopted to divide the 3D surface into small blocks to make the flattening process easy. Female dummy as well as human body were scanned and surface of the upper body was segmented using curvature plot and basic constructing line. 2D tight-fit pattern was developed using three software, the RapidForm 2004, 2C-AN and Yuka CAD. Gap between clothes and body, and the clothing pressure on the body was observed to determine the fit of the clothes. As results, clothes constructed with blocks divided by curvature plot displayed a similar level of tight fit as compared with those by basic construction line. It was found that curvature plot is effective method as a segmentation of the 3D surface even for the actual body which does not have any previous reference line. It is expected that application of curvature plot will be expanded in 3D apparel technology.

Color Segmentation of Vehicle License Plates in the RGB Color Space Using Color Component Binarization (RGB 색상 공간에서 색상 성분 이진화를 이용한차량 번호판 색상 분할)

  • Jung, Min Chul
    • Journal of the Semiconductor & Display Technology
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    • v.13 no.4
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    • pp.49-54
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    • 2014
  • This paper proposes a new color segmentation method of vehicle license plates in the RGB color space. Firstly, the proposed method shifts the histogram of an input image rightwards and then stretches the image of the histogram slide. Secondly, the method separates each of the three RGB color components and performs the adaptive threshold processing with the three components, respectively. Finally, it combines the three components under the condition of making up a segment color and removes noises with the morphological processing. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real vehicle images. The results show that the proposed algorithm is successful for most vehicle images. However, the method fails in some vehicles when the body and the license plate have the same color.