• Title/Summary/Keyword: Human Tracking

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The Modified Block Matching Algorithm for a Hand Tracking of an HCI system (HCI 시스템의 손 추적을 위한 수정 블록 정합 알고리즘)

  • Kim Jin-Ok
    • Journal of Internet Computing and Services
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    • v.4 no.4
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    • pp.9-14
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    • 2003
  • A GUI (graphical user interface) has been a dominant platform for HCI (human computer interaction). A GUI - based interaction has made computers simpler and easier to use. The GUI - based interaction, however, does not easily support the range of interaction necessary to meet users' needs that are natural. intuitive, and adaptive. In this paper, the modified BMA (block matching algorithm) is proposed to track a hand in a sequence of an image and to recognize it in each video frame in order to replace a mouse with a pointing device for a virtual reality. The HCI system with 30 frames per second is realized in this paper. The modified BMA is proposed to estimate a position of the hand and segmentation with an orientation of motion and a color distribution of the hand region for real - time processing. The experimental result shows that the modified BMA with the YCbCr (luminance Y, component blue, component red) color coordinate guarantees the real - time processing and the recognition rate. The hand tracking by the modified BMA can be applied to a virtual reclity or a game or an HCI system for the disable.

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Gaze Tracking with Low-cost EOG Measuring Device (저가형 EOG 계측장치를 이용한 시선추적)

  • Jang, Seung-Tae;Lee, Jung-Hwan;Jang, Jae-Young;Chang, Won-Du
    • Journal of the Korea Convergence Society
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    • v.9 no.11
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    • pp.53-60
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    • 2018
  • This paper describes the experiments of gaze tracking utilizing a low-cost electrooculogram measuring device. The goal of the experiments is to verify whether the low-cost device can be used for a complicated human-computer interaction tool, such as the eye-writing. Two experiments are conducted for this goal: a simple gaze tracking of four directional eye-movements, and eye-writing-which is to draw letters or shapes in a virtual space. Eye-written alphabets were obtained by two PSL-iEOGs and an Arduino Uno; they were classified by dynamic positional warping after preprocessed by a wavelet function. The results show that the expected recognition accuracy of the four-directional recognition is close to 90% when noises are controlled, and the similar median accuracy (90.00%) was achieved for the eye-writing when the number of writing patterns are limited to five. In future works, additional algorithms for stabilizing the signal need to be developed.

Methodology for Vehicle Trajectory Detection Using Long Distance Image Tracking (원거리 차량 추적 감지 방법)

  • Oh, Ju-Taek;Min, Joon-Young;Heo, Byung-Do
    • International Journal of Highway Engineering
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    • v.10 no.2
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    • pp.159-166
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    • 2008
  • Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

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Information Architecture Design Using Eye-tracking Method (Eye-Tracking Method를 이용한 메뉴구조 설계 및 평가)

  • Park, Jong-Soon;Myung, Ro-Hae
    • Journal of the HCI Society of Korea
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    • v.2 no.1
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    • pp.33-39
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    • 2007
  • Because of the cognitive overload which is caused by the complicated information structure, Digital Convergence product interferes with the effective retrieval of the information from the menu. Two methods have been used to alleviate that cognitive overload by making an effective menu structure; physical menu structure method which is related with the width and depth of the menu, semantic menu structure method which is related with the menu title. In this research, we tried to demonstrate the effectiveness of the menu structure designing method by suggesting a new semantic methodology which uses the Fixation and Fixation duration which are accompanied by the visual search. Because the Fixation is automatically processed by the human cognitive model, we could easily recognize whether the information structure is correspond to the cognitive model or not. From this fact we established the hypothesis that the number of cognitively well established menu structures are fewer than that of the wrongly designed menu structures in terms of the Fixation number and Duration. To verify this hypothesis, we compared the Fixation number and Duration of the modified menu structures with those of the original menu structures by using the Eye-Tracking experiment. As a result, we could find the significant decrease of the Fixation number and Duration after modification. Therefore we could recognize that the modified menu structure was more effective than the original menu structure. In sum, the newly suggested menu structure designing methodology which uses the Fixation and Fixation Duration accompanied by the visual search was proved to be a very effective method.

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Pedestrian Traffic Counting Using HoG Feature-Based Person Detection and Multi-Level Match Tracking (HoG 특징 기반 사람 탐지와 멀티레벨 매칭 추적을 이용한 보행자 통행량 측정 알고리즘)

  • Kang, Sung-Wook;Jung, Jin-dong;Seo, Hong-il;Lee, Hae-Yeoun
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.8
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    • pp.385-392
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    • 2016
  • Market analysis for a business plain is required for the success in the modern world. Most important part in this analysis is pedestrian traffic counting. A traditional way for this is counting it in person. However, it causes high labor costs and mistakes. This paper proposes an automatic algorithm to measure the pedestrian traffic count using images with webcam. The proposed algorithm is composed of two parts: pedestrian area detection and movement tracking. In pedestrian area detection, moving blobs are extracted and pedestrian areas are detected using HoG features and Adaboost algorithm. In movement tracking, multi-level matching and false positive removal are applied to track pedestrian areas and count the pedestrian traffic. Multi-level matching is composed of 3 steps: (1) the similarity calculation between HoG area, (2) the similarity calculation of the estimated position with Kalman filtering, and (3) the similarity calculation of moving blobs in the pedestrian area detection. False positive removal is to remove invalid pedestrian area. To analyze the performance of the proposed algorithm, a comparison is performed with the previous human area detection and tracking algorithm. The proposed algorithm achieves 83.6% accuracy in the pedestrian traffic counting, which is better than the previous algorithm over 11%.

Face Tracking Method based on Neural Oscillatory Network Using Color Information (컬러 정보를 이용한 신경 진동망 기반 얼굴추적 방법)

  • Hwang, Yong-Won;Oh, Sang-Rok;You, Bum-Jae;Lee, Ji-Yong;Park, Mig-Non;Jeong, Mun-Ho
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.2
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    • pp.40-46
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    • 2011
  • This paper proposes a real-time face detection and tracking system that uses neural oscillators which can be applied to access regulation system or control systems of user authentication as well as a new algorithm. We study a way to track faces using the neural oscillatory network which imitates the artificial neural net of information handing ability of human and animals, and biological movement characteristic of a singular neuron. The system that is suggested in this paper can broadly be broken into two stages of process. The first stage is the process of face extraction, which involves the acquisition of real-time RGB24bit color video delivering with the use of a cheap webcam. LEGION(Locally Excitatory Globally Inhibitory)algorithm is suggested as the face extraction method to be preceded for face tracking. The second stage is a method for face tracking by discovering the leader neuron that has the greatest connection strength amongst neighbor neuron of extracted face area. Along with the suggested method, the necessary element of face track such as stability as well as scale problem can be resolved.

Real-Time Human Tracker Based Location and Motion Recognition for the Ubiquitous Smart Home (유비쿼터스 스마트 홈을 위한 위치와 모션인식 기반의 실시간 휴먼 트랙커)

  • Park, Se-Young;Shin, Dong-Kyoo;Shin, Dong-Il;Cuong, Nguyen Quoe
    • Proceedings of the Korean Information Science Society Conference
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    • 2008.06d
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    • pp.444-448
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    • 2008
  • The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2:image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

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W3C based Interoperable Multimodal Communicator (W3C 기반 상호연동 가능한 멀티모달 커뮤니케이터)

  • Park, Daemin;Gwon, Daehyeok;Choi, Jinhuyck;Lee, Injae;Choi, Haechul
    • Journal of Broadcast Engineering
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    • v.20 no.1
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    • pp.140-152
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    • 2015
  • HCI(Human Computer Interaction) enables the interaction between people and computers by using a human-familiar interface called as Modality. Recently, to provide an optimal interface according to various devices and service environment, an advanced HCI method using multiple modalities is intensively studied. However, the multimodal interface has difficulties that modalities have different data formats and are hard to be cooperated efficiently. To solve this problem, a multimodal communicator is introduced, which is based on EMMA(Extensible Multimodal Annotation Markup language) and MMI(Multimodal Interaction Framework) of W3C(World Wide Web Consortium) standards. This standard based framework consisting of modality component, interaction manager, and presentation component makes multiple modalities interoperable and provides a wide expansion capability for other modalities. Experimental results show that the multimodal communicator is facilitated by using multiple modalities of eye tracking and gesture recognition for a map browsing scenario.

The Individual Discrimination Location Tracking Technology for Multimodal Interaction at the Exhibition (전시 공간에서 다중 인터랙션을 위한 개인식별 위치 측위 기술 연구)

  • Jung, Hyun-Chul;Kim, Nam-Jin;Choi, Lee-Kwon
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.19-28
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    • 2012
  • After the internet era, we are moving to the ubiquitous society. Nowadays the people are interested in the multimodal interaction technology, which enables audience to naturally interact with the computing environment at the exhibitions such as gallery, museum, and park. Also, there are other attempts to provide additional service based on the location information of the audience, or to improve and deploy interaction between subjects and audience by analyzing the using pattern of the people. In order to provide multimodal interaction service to the audience at the exhibition, it is important to distinguish the individuals and trace their location and route. For the location tracking on the outside, GPS is widely used nowadays. GPS is able to get the real time location of the subjects moving fast, so this is one of the important technologies in the field requiring location tracking service. However, as GPS uses the location tracking method using satellites, the service cannot be used on the inside, because it cannot catch the satellite signal. For this reason, the studies about inside location tracking are going on using very short range communication service such as ZigBee, UWB, RFID, as well as using mobile communication network and wireless lan service. However these technologies have shortcomings in that the audience needs to use additional sensor device and it becomes difficult and expensive as the density of the target area gets higher. In addition, the usual exhibition environment has many obstacles for the network, which makes the performance of the system to fall. Above all these things, the biggest problem is that the interaction method using the devices based on the old technologies cannot provide natural service to the users. Plus the system uses sensor recognition method, so multiple users should equip the devices. Therefore, there is the limitation in the number of the users that can use the system simultaneously. In order to make up for these shortcomings, in this study we suggest a technology that gets the exact location information of the users through the location mapping technology using Wi-Fi and 3d camera of the smartphones. We applied the signal amplitude of access point using wireless lan, to develop inside location tracking system with lower price. AP is cheaper than other devices used in other tracking techniques, and by installing the software to the user's mobile device it can be directly used as the tracking system device. We used the Microsoft Kinect sensor for the 3D Camera. Kinect is equippedwith the function discriminating the depth and human information inside the shooting area. Therefore it is appropriate to extract user's body, vector, and acceleration information with low price. We confirm the location of the audience using the cell ID obtained from the Wi-Fi signal. By using smartphones as the basic device for the location service, we solve the problems of additional tagging device and provide environment that multiple users can get the interaction service simultaneously. 3d cameras located at each cell areas get the exact location and status information of the users. The 3d cameras are connected to the Camera Client, calculate the mapping information aligned to each cells, get the exact information of the users, and get the status and pattern information of the audience. The location mapping technique of Camera Client decreases the error rate that occurs on the inside location service, increases accuracy of individual discrimination in the area through the individual discrimination based on body information, and establishes the foundation of the multimodal interaction technology at the exhibition. Calculated data and information enables the users to get the appropriate interaction service through the main server.

A New Face Tracking Method Using Block Difference Image and Kalman Filter in Moving Picture (동영상에서 칼만 예측기와 블록 차영상을 이용한 얼굴영역 검출기법)

  • Jang, Hee-Jun;Ko, Hye-Sun;Choi, Young-Woo;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.2
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    • pp.163-172
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    • 2005
  • When tracking a human face in the moving pictures with complex background under irregular lighting conditions, the detected face can be larger including background or smaller including only a part of the face. Even background can be detected as a face area. To solve these problems, this paper proposes a new face tracking method using a block difference image and a Kalman estimator. The block difference image allows us to detect even a small motion of a human and the face area is selected using the skin color inside the detected motion area. If the pixels with skin color inside the detected motion area, the boundary of the area is represented by a code sequence using the 8-neighbor window and the head area is detected analysing this code. The pixels in the head area is segmented by colors and the region most similar with the skin color is considered as a face area. The detected face area is represented by a rectangle including the area and its four vertices are used as the states of the Kalman estimator to trace the motion of the face area. It is proved by the experiments that the proposed method increases the accuracy of face detection and reduces the fare detection time significantly.