• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.236-246
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• 2006

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks such as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. In this paper, the development of new snake model called 'adaptive color snake model (ACSM)' for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. For robust tracking, the condensation algorithm was adopted to control the parameters of ACSM. The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.1
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• pp.19-26
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• 2017

In this paper, we describe the design and performance of UAV system toward compact and fully autonomous quadrotors, where they can complete logistics application, rescue work, inspection tour and remote sensing without external assistance systems like ground station computers, high-performance wireless communication devices or motion capture system. we propose high-speed hovering flyght height control method based on state feedback control with image information from active camera and multirate observer because we can get image of the information only every 30ms. Finally, we show the advantages of proposed method by simulations and experiments.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.714-718
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• 2009

3D reconstruction of a human face from an image sequence remains an important problem in computer vision. We propose a method, based on a factorization algorithm, that reconstructs a 3D face model from short image sequences exhibiting rotational motion. Factorization algorithms can recover structure and motion simultaneously from one image sequence, but they usually require that all feature points be well tracked. Under rotational motion, however, feature tracking often fails due to occlusion and frame out of features. Additionally, the paucity of images may make feature tracking more difficult or decrease reconstruction accuracy. The proposed 3D reconstruction approach can handle short image sequences exhibiting rotational motion wherein feature points are likely to be missing. We implement the proposal as a reconstruction method; it employs image sequence division and a feature tracking method that uses Active Appearance Models to avoid the failure of feature tracking. Experiments conducted on an image sequence of a human face demonstrate the effectiveness of the proposed method.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2809-2815
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• 1999

Level set, and active contour(snakes) models are extensively used for image segmentation or shape extraction in computer vision. Snakes utilize the energy minimization concepts, and level set is based on the curve evolution in order to extract contours from image data. In general, these two models have their own drawbacks. For instance, snake acts pooly unless it is placed close to the wanted shape boundary, and it has difficult problem when image has multiple objects to be extracted. But, level set method is free of initial curve position problem, and has ability to handle topology of multiple objects. Nevertheless, level set method requires much more calculation time compared to snake model. In this paper, we use good points of two described models and also apply multi resolution algorithm in order to speed up the process without decreasing the performance of the shape extraction.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.1
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• pp.99-106
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• 2003

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the there dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The insertion task of an electric line into a sleeve is selected as the typical task of the maintenance of active electric power distribution lines in this paper. A modified hough transform is applied to the recognition of the center of electric line and optimal target position calculation method is newly derived in order to recognize the center 3 dimensional position of the electric line. By the proposed method, it is proved that the center position of the electric line can be recognized without respect to the noise of image and the shape of electric lines and the insertion task of an electric tine is realized.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1163-1168
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• 2001

The ranging systems measure range data in three-dimensional coordinate from target surface. These non-contact remote ranging systems is widely used in various automation applications, including military equipment, construction field, navigation, inspection, assembly, and robot vision. The active ranging systems using time of flight technique or light pattern illumination technique are complex and expensive, the passive systems based on stereo or focusing principle are time-consuming. The proposed algorithm, that is based on cross correlation of projection profile of vertical edge, provides advantages of fast and simple operation in the range acquisition. The results of experiment show the effectiveness of the proposed algorithm.

• ETRI Journal
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• v.35 no.6
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• pp.1011-1020
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• 2013

In this paper, we present a method for obtaining a high-quality 3D depth. The advantages of active pattern projection and passive stereo matching are combined and a system is established. A diffractive optical element (DOE) is developed to project the active pattern. Cross guidance (CG) and auto guidance (AG) are proposed to perform the passive stereo matching in a stereo image in which a DOE pattern is projected. When obtaining the image, the CG emits a DOE pattern periodically and consecutively receives the original and pattern images. In addition, stereo matching is performed using these images. The AG projects the DOE pattern continuously. It conducts cost aggregation, and the image is restored through the process of removing the pattern from the pattern image. The ground truth is generated to estimate the optimal parameter among various stereo matching algorithms. Using the ground truth, the optimal parameter is estimated and the cost computation and aggregation algorithm are selected. The depth is calculated and bad-pixel errors make up 4.45% of the non-occlusion area.

• The Research Journal of the Costume Culture
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• v.26 no.3
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• pp.471-484
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• 2018

This study selected fashion brands claiming to advocate feminism to analyze their characteristics and female images. For the study's data, online foreign feminist fashion brands were sifted from March 2017 to January 2018 and 28 clothing brands were selected. The study's results show that feminist fashion brands aim at the demassification and individualization of fashion products to be more inclusive of individuals' physical characteristics and diversity. Additionally, feminist brands entice consumption through communication and participation in online communities and through the value of social coexistence. The essential female image produced by feminist fashion brands deconstructs a socially idealized female image and expresses a sense of self-body positivity. In turn, the concept of self-body positivity is communicated through natural images of independent women with distinct identities based on differences in race, culture, and sexual orientation. Moreover, feminist fashion brands produce social images featuring independent women using active wear to engage in social activities. Casual wear is also used to reflect active women, while mannish looks and power suits express women's social status and professional abilities. Ultimately, these offer functionally active and rational images, combined with female images featuring long hair and makeup. Yet another type of female image seeks to create a new vision of women as diverse due to their various cultures, countries of origin, races, and individual tastes. These new images express women's physical differences, distinct identities, and diversity while simultaneously deconstructing pre-existing forms of clothing.

• Smart Media Journal
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• v.6 no.3
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• pp.49-56
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• 2017

Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.53-62
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• 2012

Object segmentation is a demanding research area and not a trivial problem of image processing and computer vision. Tremendous segmentation algorithms were addressed on gray-scale (or biomedical) images that rely on numerous image features as well as their strategies. These works in practice cannot apply to natural color images because of their negative effects to color values due to the use of gray-scale gradient information. In this paper, we proposed a new approach for color object segmentation by modifying a geometric active contour model named distance regularized level set evolution (DRLSE). Its speed function will be designed to exploit as much as possible color gradient information of images. Finally, we provide experiments to show performance of our method with respect to its accuracy and time efficiency using various color images.