• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.818-820
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• 1999

In this paper, a new boundary tracking algorithm for extracting finger area, which may be utilized by a finger crease pattern recognition algorithm, is proposed. Due to noise and irregular illumination, conventional algorithms for boundary tracking such as skeleton-based tracking methods were not suitable for typical boundary image of hand. So we propose a new finger boundary tracking algorithm utilizing a boundary-point-detection mask. We have observed that the proposed method provides stable and optimised boundary tracking.

• ETRI Journal
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• v.33 no.3
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• pp.415-422
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• 2011

In this paper, we present a novel vision-based method of recognizing finger actions for use in electronic appliance interfaces. Human skin is first detected by color and consecutive motion information. Then, fingertips are detected by a novel scale-invariant angle detection based on a variable k-cosine. Fingertip tracking is implemented by detected region-based tracking. By analyzing the contour of the tracked fingertip, fingertip parameters, such as position, thickness, and direction, are calculated. Finger actions, such as moving, clicking, and pointing, are recognized by analyzing these fingertip parameters. Experimental results show that the proposed angle detection can correctly detect fingertips, and that the recognized actions can be used for the interface with electronic appliances.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.810-815
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• 2013

In case Wi-Fi network based First responder's position tracking system is used, range measurement must be generated from RSSI finger print database. However, it is impossible to build up finger print database and to perform rescue operation at same time in the scene of rescue. In this paper, improvised Wi-Fi network without finger print database and pedestrian dead reckoning based first responders tracking system is proposed.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.847-850
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• 2008

On today, human is going to develop machine by using mutual communication to machine. Including vision - based HCI(Human Computer Interaction), the technique which to recognize finger and to track finger is important in HCI systems, in HCI systems. In order to divide finger, this paper uses more effectively dividing the technique using subtraction which is separation of background and foreground, as well as to divide finger from limited background and cluttered background. In order to divide finger, the finger is recognized to make "Template-Matching" by identified fingertip images. And, identified gestures be compared the tracked gesture after tracking recognized finger. In this paper, after obtaining interest area, not only using subtraction image and template-matching but to perform template-matching in the area. So, emphasis is placed on decreasing perform speed and reaction speed, and we propose technique which is more effectively recognizing gestures.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.478-481
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• 2008

기존 핑거 트래킹(Finger Tracking)을 수행하는데 있어 핑거팁(Finger-tip)을 구하는 방법 중 가장 일반적인 방법은 먼저 피부색 정보(Skin Color)를 추출한다. 그 다음 블럽(Blob) 함수의 블럽 컬러링(Blob Coloring) 알고리즘을 통하여 피부 윤곽선(Skin Contour)를 구하고, 그 중 가장 최상위 점을 핑거팁으로 정한다. 그러나 이 방법은 밴딩 핑거(Bending Finger) 상태에서 핑거팁 위치를 측정할 때 실제 손가락 끝이 아닌 잘못된 위치를 잡는 문제점을 가지고 있다. 본 논문에서 제안하는 방법은 밴딩 핑거 상태에서의 핑거 트래킹시 잘못된 핑거팁을 측정하는 문제점을 사용자들의 성향을 통해 미리 예상하고 보정함으로써 성능을 향상시키고자 한다.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.703-709
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• 2015

In this work, a robot aimed at grapping and delivering an object by using a simple finger-pointing command from a hand- or arm-handicapped person is introduced. In this robot system, a Leap Motion sensor is utilized to obtain the finger-motion data of the user. In addition, a Kinect sensor is also used to measure the 3D (Three Dimensional)-position information of the desired object. Once the object is pointed at through the finger pointing of the handicapped user, the exact 3D information of the object is determined using an image processing technique and a coordinate transformation between the Leap Motion and Kinect sensors. It was found that the information obtained is transmitted to the robot controller, and that the robot eventually grabs the target and delivers it to the handicapped person successfully.

• The Journal of Korea Robotics Society
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• v.3 no.4
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• pp.315-322
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• 2008

A new soft finger mechanism using a spring as a backbone is proposed in this work. It is a 4 DOF mechanism that consists of a spring and 3 cylinders, which behave like joints with 3 up-and-down rotations and 1 left-and-right rotation. To control each joint, cylinders have small holes in their cross-sectional areas, and wires of different length are penetrated into these holes. We can control each joint by pulling the corresponding wire. The forward kinematics is solved by using the geometry of mechanism. And the relationship (Jacobian) between the linear velocity of the wires and the joint angular rate is obtained. A virtual simulator is developed to test the validity of the kinematic model. In the experiment, first, the position control is conducted by tracking a given trajectory. Second, to verify the flexibility and safety, we show that the soft finger deflects in a safe manner, in spite of the collision with environment.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.11-18
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• 2011

In the field of image processing to track the fingertip much research has been done. The most common way to calculate the fingertip first, to extract color information. Then, it uses Blob Coloring algorithms which are expressed in blob functions the skin contour and calculates. The algorithm from contour decides the highest location with the fingertip. But this method when measuring it location from the finger condition which bents is not the actual fingertip and has the problem which detects the location which goes wrong. This paper proposes the color space correction algorithm to tracks the fingertip which bents. The method which proposes when tracking the fingertip from the finger condition which bents solves the problem which measures the location which goes wrong. Aim of this paper in compliance with the propensity of the users forecasts a problem in advance and corrects with improvement at the time of height boil an efficiency. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved the image recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.1001-1008
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• 2018

In this paper, we propose an efficient location tracking scheme using wireless signals for various situations in marine environment that requires location information for many reasons such as lifesaving, accident prevention, and facility management. Our proposed location tracking scheme not only monitors user's location, but also minimizes the risk under the user's limited battery power budget. The position of a user can be obtained at base stations from the strengths of the received signals from the user. In this case, it may require to prevent the user from getting out of the predetermined safe area. For each location in the safe area, we define a risk function, which is influenced by many factors such as location accuracy, depth, flow rate, and geometry. Our proposed scheme is based on finger printing technique and aims at minimizing the average risk of each user in the safe area.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.780-788
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• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.