• Title/Summary/Keyword: Image motion analysis

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Intelligent Image Analysis System for Preventing Safety Hazards in Dangerous Working Area (작업안전 위험상황 대응을 위한 지능형 영상분석 시스템 구축에 관한 연구)

  • Jang, Hyun Song
    • Journal of the Korea Safety Management & Science
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    • v.17 no.2
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    • pp.47-54
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    • 2015
  • To prevent safety hazards in dangerous working area, we have proposed an intelligent image analysis system. Six common patterns of safety violations of workers' are defined and its motion detection algorithms are developed for alarm to CCTV monitoring system. Developed algorithms are implemented at 195 dangerous areas such as chemical and gas treated room. The results of violated motion detection ratio by developed system shows 94.95% of true positive cases, and 0.21% of false positive cases from all 587,645 event cases in one month implementation period. In the period, it is observed that the number of safety rule violations and the following accidents are decreased.

Forward-Looking Synthetic Inverse Scattering Image Formation for a Vehicle with Curved Motion Based on Time Domain Correlation (시간 영역 상관관계 기법을 통한 곡선운동을 하는 차량용 전방 관측 역산란 합성 영상 형성)

  • Lee, Hyukjung;Chun, Joohwan;Hwang, Sunghyun;You, Sungjin;Byun, Woojin
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.1
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    • pp.60-69
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    • 2019
  • In this paper, we deal with forward-looking imaging, and focus on forward-looking synthetic inverse scattering imaging for a vehicle with curved motion. For image formation, time domain correlation(TDC) is used and a 2D image of the ground in front of the vehicle is generated. Because TDC is a technique that implements matched filtering for a space-variant system, it is robust to Gaussian additive noise of measurements. Furthermore, comparison and analysis between images from linear motion and curved motion show that the resolution of the image is improved; however, the entropy of the image is increased owing to curved motion.

Stereo Vision Based 3-D Motion Tracking for Human Animation

  • Han, Seung-Il;Kang, Rae-Won;Lee, Sang-Jun;Ju, Woo-Suk;Lee, Joan-Jae
    • Journal of Korea Multimedia Society
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    • v.10 no.6
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    • pp.716-725
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    • 2007
  • In this paper we describe a motion tracking algorithm for 3D human animation using stereo vision system. This allows us to extract the motion data of the end effectors of human body by following the movement through segmentation process in HIS or RGB color model, and then blob analysis is used to detect robust shape. When two hands or two foots are crossed at any position and become disjointed, an adaptive algorithm is presented to recognize whether it is left or right one. And the real motion is the 3-D coordinate motion. A mono image data is a data of 2D coordinate. This data doesn't acquire distance from a camera. By stereo vision like human vision, we can acquire a data of 3D motion such as left, right motion from bottom and distance of objects from camera. This requests a depth value including x axis and y axis coordinate in mono image for transforming 3D coordinate. This depth value(z axis) is calculated by disparity of stereo vision by using only end-effectors of images. The position of the inner joints is calculated and 3D character can be visualized using inverse kinematics.

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A Case Study on AI-Driven <DEEPMOTION> Motion Capture Technology

  • Chen Xi;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.87-92
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    • 2024
  • The rapid development of artificial intelligence technology in recent years is evident, from the emergence of ChatGPT to innovations like Midjourney, Stable Diffution, and the upcoming SORA text-to-video technology by OPENai. Animation capture technology, driven by the AI technology trend, is undergoing significant advancements, accelerating the progress of the animation industry. Through an analysis of the current application of DEEPMOTION, this paper explores the development direction of AI motion capture technology, analyzes issues such as errors in multi-person object motion capture, and examines the vast prospects. With the continuous advancement of AI technology, the ability to recognize and track complex movements and expressions faster and more accurately, reduce human errors, enhance processing speed and efficiency. This advancement lowers technological barriers and accelerates the fusion of virtual and real worlds.

Moving Object Detection and Tracking in Image Sequence with complex background (복잡한 배경을 가진 영상 시퀀스에서의 이동 물체 검지 및 추적)

  • 정영기;호요성
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.615-618
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    • 1999
  • In this paper, a object detection and tracking algorithm is presented which exhibits robust properties for image sequences with complex background. The proposed algorithm is composed of three parts: moving object detection, object tracking, and motion analysis. The moving object detection algorithm is implemented using a temporal median background method which is suitable for real-time applications. In the motion analysis, we propose a new technique for removing a temporal clutter, such as a swaying plant or a light reflection of a background object. In addition, we design a multiple vehicle tracking system based on Kalman filtering. Computer simulation of the proposed scheme shows its robustness for MPEG-7 test image sequences.

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Embedding of Objects Using SFM Analysis in Synthetic Image Sequences (합성영상에서의 이동물체의 SFM분석을 통한 물체의 삽입)

  • 최경업;김용철
    • Proceedings of the IEEK Conference
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    • 2000.11c
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    • pp.181-184
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    • 2000
  • This paper presents an experimental system, where an object extracted from an image sequence is embedded into the desired position in a scene. First, a moving object is detected and the 3-D structure is obtained by SFM analysis of comer trajectories. We constrained the motion to translational motion only. Extracted objects are classified by matching with 3-D models and then the structure of the occluded part is restored. Camera calibration is performed for the background scene which will embed the object. Finally, the object is embedded into the scene. In the experiments, we used synthetic image sequences generated with OpenGL library for easy evaluation of the 3-D structure estimation.

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Visual expression technique analysis of motion graphic by media for emotion communication (감성전달을 위한 매체별 모션그래픽의 시각적 표현기법 분석)

  • Yun, Hwang-Rok;Kyung, Byung-Pyo;Lee, Dong-Lyeor
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.921-926
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    • 2009
  • After the scientific development of human history, numerous images have been developed and expanded in digital media as a communication tools. Image digital media make communication closer between sender and receptor. The image digital media which has been developed with the change of technology and media transformation have shortened visual information transportation and the time as well by combining the sense of visual and audio. Motion graphic field has been emerged as the type of image digital media development. The development of motion graphic make possible for the expressive effect and dynamic image technique which is impossible by the existing media type. Especially, it is applied to various field such as the title of movie, TV program, and advertise or music video etc. These image expression techniques are stimulating acceptor's emotion to take a role of emotion communication function also. This study aims to find the characteristics motion graphic of which how influence as an effective communication tool as important role to the receptors, and the examine the effect and application of motion graphic to the receptors as a emotion communication tool by case study.

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Parametric Imaging with Respiratory Motion Correction for Contrast-Enhanced Ultrasonography (조영증강 초음파 진단에서 호흡에 의한 흔들림을 보정한 파라미터 영상 생성 기법)

  • Kim, Ho-Joon;Cho, Yun-Seok
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.2
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    • pp.69-76
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    • 2020
  • In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.

Fire Detection Algorithm Based On Motion Information and Color Information Analysis (움직임 정보와 칼라정보 분석을 통한 화재검출 알고리즘)

  • Choi, Hong-seok;Moon, Kwang-seok;Kim, Jong-nam;Park, Seung-seob
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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    • pp.180-188
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    • 2016
  • In this paper, we propose a fire detection algorithm based on motion information and color information analysis. Conventional fire detection algorithms have as main problem the difficulty to detect fire due to external light, intensity, background image complexity, and little fire diffusion. So we propose a fire detection algorithm that accurate and fast. First, it analyzes the motion information in video data and then set the first candidate. Second, it determines this domain after analyzing the color and the domain. This algorithm assures a fast fire detection and a high accuracy compared with conventional fire detection algorithms. Our algorithm will be useful to real-time fire detection in real world.

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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