Robust Extrinsic Camera Calibration from Trajectories in Human-Populated Environments
Abstract. This paper proposes a novel robust approach to perform inter-camera and ground-camera calibration in the context of visual monitoring of human-populated areas. By supposing that the monitored agents evolve on a single plane and that the cameras intrinsic parameters are known, we use the im...
| Autores: | , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2012 |
| País: | México |
| Recursos: | Instituto Politécnico Nacional |
| Repositório: | Repositorio Digital del IPN |
| OAI Identifier: | oai:www.repositoriodigital.ipn.mx:123456789/14811 |
| Acesso em linha: | http://www.repositoriodigital.ipn.mx/handle/123456789/14811 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Keywords. Calibration, computer vision, tracking, videosurveillance and multiple camera systems. |
| Resumo: | Abstract. This paper proposes a novel robust approach to perform inter-camera and ground-camera calibration in the context of visual monitoring of human-populated areas. By supposing that the monitored agents evolve on a single plane and that the cameras intrinsic parameters are known, we use the image trajectories of moving objects as tracked by standard trackers in a RANSAC paradigm to estimate the extrinsic parameters of the different cameras. We illustrate the performance of our algorithm on several challenging experimental setups and compare it to existing approaches. |
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