• Title/Summary/Keyword: 객체 움직임

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Gait Recognition Using Multiple Feature detection (다중 특징점 검출을 이용한 보행인식)

  • Cho, Woon;Kim, Dong-Hyeon;Paik, Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.6
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    • pp.84-92
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    • 2007
  • The gait recognition is presented for human identification from a sequence of noisy silhouettes segmented from video by capturing at a distance. The proposed gait recognition algorithm gives better performance than the baseline algorithm because of segmentation of the object by using multiple modules; i) motion detection, ii) object region detection, iii) head detection, and iv) active shape models, which solve the baseline algorithm#s problems to make background, to remove shadow, and to be better recognition rates. For the experiment, we used the HumanID Gait Challenge data set, which is the largest gait benchmarking data set with 122 objects, For realistic simulation we use various values for the following parameters; i) viewpoint, ii) shoe, iii) surface, iv) carrying condition, and v) time.

Haptic Media Broadcasting (촉각방송)

  • Cha, Jong-Eun;Kim, Yeong-Mi;Seo, Yong-Won;Ryu, Je-Ha
    • Broadcasting and Media Magazine
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    • v.11 no.4
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    • pp.118-131
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    • 2006
  • With rapid development in ultra fast communication and digital multimedia, the realistic broadcasting technology, that can stimulate five human senses beyond the conventional audio-visual service is emerging as a new generation broadcasting technology. In this paper, we introduce a haptic broadcasting system and related core system and component techniques by which we can 'touch and feel' objects in an audio-visual scene. The system is composed of haptic media acquisition and creation, contents authoring, in the haptic broadcasting, the haptic media can be 3-D geometry, dynamic properties, haptic surface properties, movement, tactile information to enable active touch and manipulation and passive movement following and tactile effects. In the proposed system, active haptic exploration and manipulation of a 3-D mesh, active haptic exploration of depth video, passive kinesthetic interaction, and passive tactile interaction can be provided as potential haptic interaction scenarios and a home shopping, a movie with tactile effects, and conducting education scenarios are produced to show the feasibility of the proposed system.

Intelligent interface using hand gestures recognition based on artificial intelligence (인공지능 기반 손 체스처 인식 정보를 활용한 지능형 인터페이스)

  • Hangjun Cho;Junwoo Yoo;Eun Soo Kim;Young Jae Lee
    • Journal of Platform Technology
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    • v.11 no.1
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    • pp.38-51
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    • 2023
  • We propose an intelligent interface algorithm using hand gesture recognition information based on artificial intelligence. This method is functionally an interface that recognizes various motions quickly and intelligently by using MediaPipe and artificial intelligence techniques such as KNN, LSTM, and CNN to track and recognize user hand gestures. To evaluate the performance of the proposed algorithm, it is applied to a self-made 2D top-view racing game and robot control. As a result of applying the algorithm, it was possible to control various movements of the virtual object in the game in detail and robustly. And the result of applying the algorithm to the robot control in the real world, it was possible to control movement, stop, left turn, and right turn. In addition, by controlling the main character of the game and the robot in the real world at the same time, the optimized motion was implemented as an intelligent interface for controlling the coexistence space of virtual and real world. The proposed algorithm enables sophisticated control according to natural and intuitive characteristics using the body and fine movement recognition of fingers, and has the advantage of being skilled in a short period of time, so it can be used as basic data for developing intelligent user interfaces.

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Recognition of Events by Human Motion for Context-aware Computing (상황인식 컴퓨팅을 위한 사람 움직임 이벤트 인식)

  • Cui, Yao-Huan;Shin, Seong-Yoon;Lee, Chang-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.4
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    • pp.47-57
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    • 2009
  • Event detection and recognition is an active and challenging topic recent in Computer Vision. This paper describes a new method for recognizing events caused by human motion from video sequences in an office environment. The proposed approach analyzes human motions using Motion History Image (MHI) sequences, and is invariant to body shapes. types or colors of clothes and positions of target objects. The proposed method has two advantages; one is thant the proposed method is less sensitive to illumination changes comparing with the method using color information of objects of interest, and the other is scale invariance comparing with the method using a prior knowledge like appearances or shapes of objects of interest. Combined with edge detection, geometrical characteristics of the human shape in the MHI sequences are considered as the features. An advantage of the proposed method is that the event detection framework is easy to extend by inserting the descriptions of events. In addition, the proposed method is the core technology for event detection systems based on context-aware computing as well as surveillance systems based on computer vision techniques.

HEVC Encoder Optimization using Depth Information (깊이정보를 이용한 HEVC의 인코더 고속화 방법)

  • Lee, Yoon Jin;Bae, Dong In;Park, Gwang Hoon
    • Journal of Broadcast Engineering
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    • v.19 no.5
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    • pp.640-655
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    • 2014
  • Many of today's video systems have additional depth camera to provide extra features such as 3D support. Thanks to these changes made in multimedia system, it is now much easier to obtain depth information of the video. Depth information can be used in various areas such as object classification, background area recognition, and so on. With depth information, we can achieve even higher coding efficiency compared to only using conventional method. Thus, in this paper, we propose the 2D video coding algorithm which uses depth information on top of the next generation 2D video codec HEVC. Background area can be recognized with depth information and by performing HEVC with it, coding complexity can be reduced. If current CU is background area, we propose the following three methods, 1) Earlier stop split structure of CU with PU SKIP mode, 2) Limiting split structure of CU with CU information in temporal position, 3) Limiting the range of motion searching. We implement our proposal using HEVC HM 12.0 reference software. With these methods results shows that encoding complexity is reduced more than 40% with only 0.5% BD-Bitrate loss. Especially, in case of video acquired through the Kinect developed by Microsoft Corp., encoding complexity is reduced by max 53% without a loss of quality. So, it is expected that these techniques can apply real-time online communication, mobile or handheld video service and so on.

Augmented Reality Game Interface Using Hand Gestures Tracking (사용자 손동작 추적에 기반한 증강현실 게임 인터페이스)

  • Yoon, Jong-Hyun;Park, Jong-Seung
    • Journal of Korea Game Society
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    • v.6 no.2
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    • pp.3-12
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    • 2006
  • Recently, Many 3D augmented reality games that provide strengthened immersive have appeared in the 3D game environment. In this article, we describe a barehanded interaction method based on human hand gestures for augmented reality games. First, feature points are extracted from input video streams. Point features are tracked and motion of moving objects are computed. The shape of the motion trajectories are used to determine whether the motion is intended gestures. A long smooth trajectory toward one of virtual objects or menus is classified as an intended gesture and the corresponding action is invoked. To prove the validity of the proposed method, we implemented two simple augmented reality applications: a gesture-based music player and a virtual basketball game. In the music player, several menu icons are displayed on the top of the screen and an user can activate a menu by hand gestures. In the virtual basketball game, a virtual ball is bouncing in a virtual cube space and the real video stream is shown in the background. An user can hit the virtual ball with his hand gestures. From the experiments for three untrained users, it is shown that the accuracy of menu activation according to the intended gestures is 94% for normal speed gestures and 84% for fast and abrupt gestures.

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Content Based Video Retrieval by Example Considering Context (문맥을 고려한 예제 기반 동영상 검색 알고리즘)

  • 박주현;낭종호;김경수;하명환;정병희
    • Journal of KIISE:Computer Systems and Theory
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    • v.30 no.12
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    • pp.756-771
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    • 2003
  • Digital Video Library System which manages a large amount of multimedia information requires efficient and effective retrieval methods. In this paper, we propose and implement a new video search and retrieval algorithm that compares the query video shot with the video shots in the archives in terms of foreground object, background image, audio, and its context. The foreground object is the region of the video image that has been changed in the successive frames of the shot, the background image is the remaining region of the video image, and the context is the relationship between the low-level features of the adjacent shots. Comparing these features is a result of reflecting the process of filming a moving picture, and it helps the user to submit a query focused on the desired features of the target video clips easily by adjusting their weights in the comparing process. Although the proposed search and retrieval algorithm could not totally reflect the high level semantics of the submitted query video, it tries to reflect the users' requirements as much as possible by considering the context of video clips and by adjusting its weight in the comparing process.

An Approach Using LSTM Model to Forecasting Customer Congestion Based on Indoor Human Tracking (실내 사람 위치 추적 기반 LSTM 모델을 이용한 고객 혼잡 예측 연구)

  • Hee-ju Chae;Kyeong-heon Kwak;Da-yeon Lee;Eunkyung Kim
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.43-53
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    • 2023
  • In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.