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Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes
Emanuel Aldea, K. H. Kiyani

Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes

Author / Organization:
Science & Mathematics Published 2014 Verification Pending

Overview & Synopsis

In this paper we address the problem of multiple camera calibration in the presence of a homogeneous scene, and without the possibility of employing calibration object based methods. The proposed solution exploits salient features present in a larger field of view, but instead of employing active vision we replace the cameras with stereo rigs featuring a long focal analysis camera, as well as a short focal registration camera. Thus, we are able to propose an accurate solution which does not require intrinsic variation models as in the case of zooming cameras. Moreover, the availability of the two views simultaneously in each rig allows for pose re-estimation between rigs as often as necessary. The algorithm has been successfully validated in an indoor setting, as well as on a difficult scene featuring a highly dense pilgrim crowd in Makkah.

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Document Information

Document Title Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes
Author / Organization Emanuel Aldea, K. H. Kiyani
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2014
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-41110
Original Source Link Visit Source Page on hal.science »