• Title/Summary/Keyword: Multiple-cameras

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User classification and location tracking algorithm using deep learning (딥러닝을 이용한 사용자 구분 및 위치추적 알고리즘)

  • Park, Jung-tak;Lee, Sol;Park, Byung-Seo;Seo, Young-ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.78-79
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    • 2022
  • In this paper, we propose a technique for tracking the classification and location of each user through body proportion analysis of the normalized skeletons of multiple users obtained using RGB-D cameras. To this end, each user's 3D skeleton is extracted from the 3D point cloud and body proportion information is stored. After that, the stored body proportion information is compared with the body proportion data output from the entire frame to propose a user classification and location tracking algorithm in the entire image.

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3D Rigid Body Tracking Algorithm Using 2D Passive Marker Image (2D 패시브마커 영상을 이용한 3차원 리지드 바디 추적 알고리즘)

  • Park, Byung-Seo;Kim, Dong-Wook;Seo, Young-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.587-588
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    • 2022
  • In this paper, we propose a rigid body tracking method in 3D space using 2D passive marker images from multiple motion capture cameras. First, a calibration process using a chess board is performed to obtain the internal variables of individual cameras, and in the second calibration process, the triangular structure with three markers is moved so that all cameras can observe it, and then the accumulated data for each frame is calculated. Correction and update of relative position information between cameras. After that, the three-dimensional coordinates of the three markers were restored through the process of converting the coordinate system of each camera into the 3D world coordinate system, the distance between each marker was calculated, and the difference with the actual distance was compared. As a result, an error within an average of 2mm was measured.

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Mobile Robot Localization using Ubiquitous Vision System (시각기반 센서 네트워크를 이용한 이동로봇의 위치 추정)

  • Dao, Nguyen Xuan;Kim, Chi-Ho;You, Bum-Jae
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.2780-2782
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    • 2005
  • In this paper, we present a mobile robot localization solution by using a Ubiquitous Vision System (UVS). The collective information gathered by multiple cameras that are strategically placed has many advantages. For example, aggregation of information from multiple viewpoints reduces the uncertainty about the robots' positions. We construct UVS as a multi-agent system by regarding each vision sensor as one vision agent (VA). Each VA performs target segmentation by color and motion information as well as visual tracking for multiple objects. Our modified identified contractnet (ICN) protocol is used for communication between VAs to coordinate multitask. This protocol raises scalability and modularity of thesystem because of independent number of VAs and needless calibration. Furthermore, the handover between VAs by using ICN is seamless. Experimental results show the robustness of the solution with respect to a widespread area. The performance in indoor environments shows the feasibility of the proposed solution in real-time.

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Position Clustering of Moving Object based on Global Color Model (글로벌 칼라기반의 이동물체 위치 클러스터링)

  • Jin, Tae-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.868-871
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    • 2009
  • We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly.

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Omni-directional Visual-LiDAR SLAM for Multi-Camera System (다중 카메라 시스템을 위한 전방위 Visual-LiDAR SLAM)

  • Javed, Zeeshan;Kim, Gon-Woo
    • The Journal of Korea Robotics Society
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    • v.17 no.3
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    • pp.353-358
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    • 2022
  • Due to the limited field of view of the pinhole camera, there is a lack of stability and accuracy in camera pose estimation applications such as visual SLAM. Nowadays, multiple-camera setups and large field of cameras are used to solve such issues. However, a multiple-camera system increases the computation complexity of the algorithm. Therefore, in multiple camera-assisted visual simultaneous localization and mapping (vSLAM) the multi-view tracking algorithm is proposed that can be used to balance the budget of the features in tracking and local mapping. The proposed algorithm is based on PanoSLAM architecture with a panoramic camera model. To avoid the scale issue 3D LiDAR is fused with omnidirectional camera setup. The depth is directly estimated from 3D LiDAR and the remaining features are triangulated from pose information. To validate the method, we collected a dataset from the outdoor environment and performed extensive experiments. The accuracy was measured by the absolute trajectory error which shows comparable robustness in various environments.

A real-time multiple vehicle tracking method for traffic congestion identification

  • Zhang, Xiaoyu;Hu, Shiqiang;Zhang, Huanlong;Hu, Xing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2483-2503
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    • 2016
  • Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

A tracking method for moving objects using multiple cameras (다중 카메라를 이용한 이미지 객체의 이동 경로 추적)

  • Oh, Jong-Hyun;Park, Ho-Hyun
    • Proceedings of the KAIS Fall Conference
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    • 2009.05a
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    • pp.407-410
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    • 2009
  • 본 논문에서는 인덱싱 카메라나, 감시 시스템의 네트워크로 부터 입력받은 영상들에서 사용자가 원하는 오브젝트를 추출해내고, 카메라의 위치와 시간으로 정렬되어진 데이터베이스상의 이미지들과 비교 분석하여 원하는 객체와의 유사도를 측정하고, 이것을 바탕으로 동일한 오브젝트들을 가진 이미지들의 집합을 시간과 공간데이터를 이용하여 객체의 이동경로를 파악하는 시스템을 제시한다.

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Fingerprint Image Sequence Mosaicking in Touchless Fingerprint Sensor (비접촉식 지문센서에서의 지문 영상 시퀀스 융합)

  • Choi, Kyoung-Taek;Choi, Hee-Seung;Kim, Jai-Hie
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.377-378
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    • 2007
  • This paper proposes an system to generate rolled-equivalent fingerprints by mosaicking sequential images captured by an toothless device. To capture rolled-equivalent fingerprints, previous works use multiple cameras. However, the method in this paper captures sequential fingerprint images with a single camera and mosaic the images by estimating the transform between images through optical flow.

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Smart Cameras-based Single Authentication in Multiple Convergence Spaces (스마트 카메라 기반 다중 융합 공간에서의 단일 인증 방식)

  • Kim, Geon-Woo;Han, Jong-Wook
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06c
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    • pp.272-273
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    • 2012
  • 본 논문에서는 이동 객체가 다중 공간을 이동할 때 초기 인증 정보를 기반으로 연속적으로 인증 서비스를 제공받기 위한 방식을 제안한다. 이는 객체의 이동 경로에 설치되어 있는 스마트 카메라의 연속 추적 기능을 사용함으로써 가능하다.

Object Tracking Framework of Video Surveillance System based on Non-overlapping Multi-camera (비겹침 다중 IP 카메라 기반 영상감시시스템의 객체추적 프레임워크)

  • Han, Min-Ho;Park, Su-Wan;Han, Jong-Wook
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.6
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    • pp.141-152
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    • 2011
  • Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.