• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.928-930
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• 2005

얼굴의 특징점 추적은 많은 응용프로그램에서 사용된다. AAM기반의 접근방식은 정교한 얼굴 특징점 정보를 제공하지만 정확한 특징 점 추출을 위해 얼굴 모양 파라미터 초기화 문제와 연속 영상에서 얼굴의 이동이 클 경우 모션 보정에 대한 문제가 여전히 남아있다. 이러한 문제를 풀기 위해 본 논문에서는 CAMShift를 사용해 얼굴 영역을 추적하고, 얼굴 영역 내에서 입을 검출함으로써 AAM 검색을 위한 얼굴 모양 파라미터를 추정하는 방법을 제안한다. 기존 알고리즘과의 비교 실험을 통해 얼굴의 움직임이 심한 상황에서도 제안하는 알고리즘의 성능이 매우 우수함을 확인할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.633-636
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• 2010

본 논문에서 Pan, Tilt 카메라를 이용한 객체 추적을 위하여 초기 지역정보를 이용하여 객체를 검출하고 검출된 객체의 색 정보를 이용하여 능동 객체를 추적하는 기술을 제안한다. 외부 환경의 잡음을 제거하기 위해 적응적인 가우시안 혼합 모델링을 이용하여 배경과 객체를 분리한다. 객체가 정해지면 카메라가 이동하는 동안에도 추적이 가능한 CAMShift 추적 알고리즘을 이용하여 객체를 실시간으로 추적한다. CAMShift 추적 알고리즘은 객체의 크기를 계산하므로 객체의 크기가 변하더라도 유동적인 객체 판별이 가능하다. Pan, Tilt의 위치는 구좌표계(Spherical coordinates system)를 이용하여 계산하였다. 이렇게 구해진 Pan, Tilt 위치는 Pan, Tilt 프로토콜을 이용하여 객체의 위치를 화면의 중심에 놓이게 함으로써 적합한 추적을 가능하게 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.666-671
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• 2008

In this paper, we propose a new method for tracking objects continously and successively based on fusion of region information, color information and motion template when multiple objects are occluded and splitted. For each frame, color template is updated and compared with the present object. The predicted region, dynamic template and color histogram are used to classify the objects. The vertical histogram of the silhouettes is analyzed to determine whether or not the foreground region contains multiple objects. The proposed method can recognize more correctly the objects to be tracked.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.851-859
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• 2002

This paper discusses the design of a working system that visually recognizes hand gestures for the control of a window based user interface. We present a method for tracking the fingertip of the index finger using a single camera. Our method is based on CAMSHIFT algorithm and performs better than the CAMSHIFT algorithm in that it tracks well particular hand poses used in the system in complex backgrounds. We describe how the location of the fingertip is mapped to a location on the monitor, and how it Is both necessary and possible to smooth the path of the fingertip location using a physical model of a mouse pointer. Our method is able to track in real time, yet not absorb a major share of computational resources. The performance of our system shows a great promise that we will be able to use this methodology to control computers in near future.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.787-796
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• 2014

Many mobile robot navigation methods utilize laser scanners, ultrasonic sensors, vision camera, and so on for detecting obstacles and path following. However, human utilizes only vision(e.g. eye) information for navigation. In this paper, we study a mobile robot control method based on only the camera vision. The Gaussian Mixture Model and a shadow removal technology are used to divide the foreground and the background from the camera image. The mobile robot uses a combined CAMSHIFT and KLT feature tracker algorithms based on the information of the foreground to follow a person. The algorithm is verified by experiments where a person is tracked and followed by a robot in a hallway.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1171-1176
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• 2014

The eye-tracking [ET] is used on the human computer interaction [HCI] analysing the movement status as well as finding the gaze direction of the eye by tracking pupil's movement on a human face. Nowadays, the ET is widely used not only in market analysis by taking advantage of pupil tracking, but also in grasping intention, and there have been lots of researches on the ET. Although the vision based ET is known as convenient in application point of view, however, not robust in changing environment such as illumination, geometrical rotation, occlusion and scale changes. This paper proposes two steps in the ET, at first, face and eye regions are discriminated by Haar classifier on the face, and then the pupils from the discriminated eye regions are tracked by CAMShift as well as Template matching. We proved the usefulness of the proposed algorithm by lots of real experiments in changing environment such as illumination as well as rotation and scale changes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.175-186
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• 2004

We present a hybrid approach of texture-based method and connected component (CC)-based method for text extraction in complex images. Two primary methods, which are mainly utilized in this area, are sequentially merged for compensating for their weak points. An automatically constructed MLP-based texture classifier can increase recall rates for complex images with small amount of user intervention and without explicit feature extraction. CC-based filtering based on the shape information using NMF enhances the precision rate without affecting overall performance. As a result, a combination of texture and CC-based methods leads to not only robust but also efficient text extraction. We also enhance the processing speed by adopting appropriate region marking methods for each input image category.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.143-146
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• 2012

Ball-Plate를 기반으로 하는 균형제어 로봇은 크게 공의 상태를 파악하는 부분과 균형을 유지하는 제어부분 2가지로 구성되어진다. 본 논문은 공의 상태를 파악하기 위해서 단일 카메라를 이용하여 CAMShift 알고리즘으로 볼을 추적한다. 그리고 칼만 필터를 사용하여 발생하는 오차를 줄이는 방법을 제안하고 그 실험 결과에 대해서 설명한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.861-877
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• 2016

This paper first discusses the disadvantages of the existing CamShift Algorithm for real time face tracking, and then proposes a new Camshift Algorithm that performs better than the existing algorithm. The existing CamShift Algorithm shows unstable tracking when tracing similar colors in the background of objects. This drawback of the existing CamShift is resolved by using Kinect’s pixel-by-pixel depth information and the Skin Detection algorithm to extract candidate skin regions based on HSV color space. Additionally, even when the tracking object is not found, or when occlusion occurs, the feature point-based matching algorithm makes it robust to occlusion. By applying the improved CamShift algorithm to face tracking, the proposed real-time face tracking algorithm can be applied to various fields. The results from the experiment prove that the proposed algorithm is superior in tracking performance to that of existing TLD tracking algorithm, and offers faster processing speed. Also, while the proposed algorithm has a slower processing speed than CamShift, it overcomes all the existing shortfalls of the existing CamShift.