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Detecting a Human Body Direction Using a Feature Selection Method
Yuuki Nakashima,Joo Kooi Tan,Seiji Ishikawa,Takashi Morie 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
This paper describes a novel technique for detecting a human body direction using SVM constructed by HOG feature selected by AdaBoost. HOG feature is well-known feature for the robust judgment of a human. We employ the feature for detecting a human body direction. We compared some feature selecting methods with the previous one. Experimental results show effectiveness of the proposed method.
Applying HOG Feature to the Detection and Tracking of a Human on a Bicycle
Heewook Jung,Joo Kooi Tan,Seiji Ishikawa,Takashi Morie 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
Detection of a human on a bicycle is an important research subject in an advanced safety vehicle driving system to decrease traffic accidents. The Histograms of Oriented Gradients (HOG) feature has been proposed as useful feature for detecting a standing human in various kinds of background. So, many researchers use currently the HOG feature to detect a human. Detecting a human on a bicycle is more difficult than detecting a human because a bicycle’s appearance can change dramatically according to viewpoints. In this paper, we propose a method of detecting a human on a bicycle using HOG feature and RealAdaboost algorithm. When detecting a human on a bicycle, occlusion is a cause of decreasing detection efficiency. Occlusion is a serious matter in car vision research because there are occlusions in real transportation environment. We decide the next position of a human on a bicycle using object tracking. Experimental results and evaluation show satisfactory performance of the proposed method.
Detection of Pedestrians Employing a Wide-angel Camera
Ryuichi Matsuda,Joo Kooi Tan,Hyoungseop Kim,Seiji Ishikawa 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
Recently, the number of accidents that pedestrians have law violation is in the tendency of decrease in Japan. However, accidents caused by pedestrians crossing a crosswalk or dashing into a crosswalk still have high ratio, and both accident sources account for 15% of the whole number of accidents caused by a pedestrian. Although many researches in ITS in which pedestrians are detected from in-vehicle cameras have been actively done to solve these problems, they usually employ standard cameras, and those pedestrians who exist outside of the camera view cannot be detected. In this paper, we employ a wide-angle camera which has wider view than a general camera and propose a technique for detecting pedestrians from the wide-angle image. Since, in a wide-angle camera image, every object becomes smaller, we propose a technique for detecting pedestrians employing optical flows converging to a FOE (Focus of Expansion). Experimental results show satisfactory performance of the technique.
Detecting Pedestrians from a Video by Stereo Cameras
Kazuki Inumaru,Joo Kooi Tan,Hyoungseop Hyoungseop,Seiji Ishikawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
The technologies for safe driving assistance are of particular importance to escape pedestrians from traffic accidents. We have been doing research on detecting pedestrians by use of stereo cameras on an automobile and giving them priorities according to their degree of danger by analyzing their motions/behaviors. In this particular paper, we present a technique for detecting pedestrians employing stereo camera images. From a disparity map, each pixel on the image is voted on a depth image employing a 2-D Gaussian distribution and the region having a peak value of the vote is chosen as an object region. This region is represented by HOG features and judged if it is a human by SVM. Experimental results show satisfactory performance of the technique.
Recognizing Facial Expression for Man-machine Interaction
Wataru Hirata,Joo Kooi Tan,Hyongseop Kim,Seiji Ishikawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, we propose a positive face expression recognition method based on the image around the mouth. We also estimate the direction of the face of a person to examine whether or not he/she has interest toward this side. In the proposed method, estimation of the position and the direction of a face is realized by using particle filter and FAST operator. The image around the mouth is detected based on the estimated face position. The feature is calculated by Gabor Filter and the facial expression is recognized by support vector machine. In the recognition of positive expression like smile or laugh, we confirmed the effectiveness of the proposed method.
Entire 3-D Modeling of an Object by Surround Cameras
Toshimasa Sone,Joo Kooi Tan,Hyongseop Kim,Seiji Ishikawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper proposes a novel 3-D modeling technique of an object. The existent 3-D modeling techniques such as stereo vision or the factorization recover 3-D shapes of part of an object observed commonly from multiple orientations. This inevitably needs registration among recovered partial shapes in order to obtain an entire 3-D model of the object. The proposed technique recovers entire shape of an object without registration by the employment of the cameras that surround the object. The cameras are calibrated using the captured images. Experimental results show satisfactory performance of the technique.
Recovering 3-D Shape of a Non-rigid Object by a Single Mobile Camera
Tsukasa Horinouchi,Joo Kooi Tan,Hyoungseop Kim,Seiji Ishikawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper describes a technique for recovering 3-D shape of a non rigid object employing a single camera. 3-D modeling of a non-rigid object has been studied employing multiple cameras. However it can be realized even by a single camera on condition that the object concerned is composed of a set of rigid objects. Experimental results show effectiveness of the proposed technique.
Human Motion Recognition Using Directional Motion History Images
Makoto Murakami,Joo Kooi Tan,Hyoungseop Kim,Seiji Ishikawa 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
Nowadays many persons are needed to observe images from surveillance cameras, because many surveillance cameras are installed in a town or in buildings. They are working under strain, because they must always watch the images from surveillance cameras to find a person with abnormal motion. Therefore reduction of the load is necessary. Many existing researches on human motion recognition are only recognition and the information of the result is not used. We assume that human motion is a set of basic motions. So, an overall motion can be understood using the recognition result of basic motions. The goal of the present research is to develop a method of human motion representation and translation using directional motion history images (DMHIs). In this paper, we describe a method of recognizing basic motions using the DMHIs. We perform the recognition by the Histograms of Oriented Gradients (HOG) feature. In the experiment, the number of bins and local area (cell) sizes for calculating the HOG feature are changed and the most suitable values are inspected.