• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.3
• /
• pp.271-274
• /
• 2006

This paper deals with a similarity decision method between the shape of hand-postures and their structures to improve performance of the vision-based hand-posture recognition system. Hand-posture recognition by vision sensors has difficulties since the human hand is an object with high degrees of freedom, and hence grabbed images present complex self-occlusion effects and, even for one hand-posture, various appearances according to viewing directions. Therefore many approaches limit the relative angle between cameras and hands or use multiple cameras. The former approach, however, restricts user's operation area. The latter requires additional considerations on the way of merging the results from each camera image to get the final recognition result. To recognize hand-postures, we use both of appearance and structural features and decide the similarity between the two types of features by learning.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.1
• /
• pp.181-192
• /
• 2017

Recently, many researches are carried out for Advanced Driver Assistant Systems(ADAS). Especially, many studies are carried out to analyze the road situation using road images. In order to improve the performance of the road situation analysis, it is necessary to acquire images with appropriate exposure time. In this paper, we design and implement multi exposure smart vehicular camera which provides road traffic information to driver. Proposed device can acquire road traffic information by on-board camera and various sensors. And we propose an auto exposure control algorithm for the road environment to increase accuracy of image recognition. In addition, we also propose the switching ROI method that apply existing ROI techniques to overcome a limited computation power of embedded devices. We developed prototype of multi exposure smart vehicular camera and performed experiments to evaluate proposed auto exposure control algorithm and switching ROI method. The results show that the average accuracy of image recognition increased by 13.45%.

• Journal of Korea Game Society
• /
• v.9 no.4
• /
• pp.67-80
• /
• 2009

In this paper, we described the development of a Korean Manual Alphabet (KMA) learning game with avatar. KMA letters correspond to the vocabulary of Korean Sign Language (KSL) when spelling a word. Each KMA letter corresponds to a letter of the Korean Alphabet (KA) and KA is represented as hand shapes by sign language user. We developed a KMA learning game for a beginner to learn KMA letters from sign language avatar and practice KMA presentation easily. The system composed of sign language teacher avatar GUI popup window based on OpenGL, KMA letter recognition module, KA letter raining game module and USB camera. A user learns a KMA letter with expressing KA syllabic from avatar and inputs a KMA letter to the system using USB camera. We evaluated the efficiency of the developed system through the verification of users.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.1
• /
• pp.56-63
• /
• 2003

This paper introduces a vision based autonomous mini mobile robot that is an approach to produce real autonomous vehicle. Previous autonomous vehicles are dependent on PC, because of complexity of designing hardware, difficulty of installation and abundant calculations. In this paper, we present an autonomous motile robot system that has abilities of accurate steering, quick movement in high speed and intelligent recognition as a stand-alone system using a mono camera. The proposed system has been implemented on mini track of which width is 25~30cm, and length is about 200cm. Test robot can run at average 32.9km/h speed on straight lane and average 22.3km/h speed on curved lane with 30~40m radius. This system provides a model of autonomous mobile robot adapted a lane recognition algorithm in odor to make real autonomous vehicle easily.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.4
• /
• pp.97-103
• /
• 2008

This study is to present a fainting motion recognizing method by using fish-eye lens images to sense emergency situations. The camera with fish-eye lens located at the center of the ceiling of the living room sends images, and then the foreground pixels are extracted by means of the adaptive background modeling method based on the Gaussian complex model, which is followed by tracing of outer points in the foreground pixel area and the elliptical mapping. During the elliptical tracing, the fish-eye lens images are converted to fluoroscope images. the size and location changes, and moving speed information are extracted to judge whether the movement, pause, and motion are similar to fainting motion. The results show that compared to using fish-eye lens image, extraction of the size and location changes. and moving speed by means of the conversed fluoroscope images has good recognition rates.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.4
• /
• pp.607-616
• /
• 2014

Face recognition is a big challenge in surveillance system since different rotation angles of the face make the difficulty to recognize the face of the same person. This paper proposes a novel method to recognize face with different head poses by using 3D information of the face. Firstly, head pose estimation (estimation of different head pose angles) is accomplished by the POSIT algorithm. Then, 3D face image data is constructed by using head pose estimation. After that, 2D image and the constructed 3D face matching is performed. Face verification is accomplished by using commercial face recognition SDK. Performance evaluation of the proposed method indicates that the error range of head pose estimation is below 10 degree and the matching rate is about 95%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.6
• /
• pp.609-616
• /
• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.1
• /
• pp.197-205
• /
• 2006

This paper presents the moving object tracking method using vision system. In order to track object in real time, the image of moving object have to be located the origin of the image coordinate axes. Accordingly, Fuzzy Control System is investigated for tracking the moving object, which control the camera module with Pan/Tilt mechanism. Hereafter, so the this system is applied to mobile robot, we design and implement image processing board for vision system. Also fuzzy controller is implemented to the StrongArm board. Finally, the proposed fuzzy controller is useful for the real-time moving object tracking system by experiment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.3
• /
• pp.202-208
• /
• 2013

In the image processing for VS (Video Surveillance), the detection of moving entities in a monitored scene is an important step. A background subtraction technique has been widely employed to find the moving entities. However, the extracted foreground regions often include not only real entities but also their cast shadows, and this can cause errors in following image processing steps, such as tracking, recognition, and analysis. In this paper, a novel technique is proposed to determine the shadow pixels of moving objects in the foreground image of a VS camera. Compared to existing techniques where the same decision criteria are applied to all moving pixels, the proposed technique determines shadow pixels using local features based on two facts: First, the amount of pixel intensity drop due to a shadow depends on the intensity level of background. Second, the distribution pattern of pixel intensities remains even if a shadow is cast. The proposed method has been tested at various situations with different backgrounds and moving humans in different colors.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.1-6
• /
• 2008

This paper proposes a game controller that provides user motion input and tactile feedback display, in addition to the traditional button-type input. The device utilizes both an accelerometer and an infrared camera in order to estimate 3D position and to recognize user motion. The information from the accelerometer and the camera are integrated for better performance. Various tactile sensations are presented using a voice-coil type vibrator. We apply the proposed controller to a motion-based game and validate its usability.