Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Multiview Trajectory Mapping Using Homography with Lens Distortion Correction | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008 Article ID 145715 11 pages doi 10.1155 2008 145715 Research Article Multiview Trajectory Mapping Using Homography with Lens Distortion Correction Gabin Kayumbi and Andrea Cavallaro Multimedia and Vision Group Department of Electronic Engineering Queen Mary University of London Mile End Road London E1 4NS UK Correspondence should be addressed to Gabin Kayumbi gabin.kayumbi@elec.qmul.ac.uk Received 17 March 2008 Accepted 8 September 2008 Recommended by Jian Zhang We present a trajectory mapping algorithm for a distributed camera setting that is based on statistical homography estimation accounting for the distortion introduced by camera lenses. Unlike traditional approaches based on the direct linear transformation DLT algorithm and singular value decomposition SVD the planar homography estimation is derived from renormalization. In addition to this the algorithm explicitly introduces a correction parameter to account for the nonlinear radial lens distortion thus improving the accuracy of the transformation. We demonstrate the proposed algorithm by generating mosaics of the observed scenes and by registering the spatial locations of moving objects trajectories from multiple cameras on the mosaics. Moreover we objectively compare the transformed trajectories with those obtained by SVD and least mean square LMS methods on standard datasets and demonstrate the advantages of the renormalization and the lens distortion correction. Copyright 2008 G. Kayumbi and A. Cavallaro. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Monitoring large areas such as airports and underground stations requires a set of distributed cameras to capture common patterns of activities and detect unusual events or anomalous .
