Artículos

 

Robust Extrinsic Camera Calibration from Trajectories in Human–Populated Environments

 

Calibración extrínseca robusta de un sistema de cámaras a partir de trayectorias en ambientes humanos

 

Guillermo Baqueiro Victorín¹ and Jean Bernard Hayet²

 

¹ Digipro, Distrito Federal, Mexico. Correo: baqueiro@cimat.mx.

² Centro de Investigación en Matemáticas (CIMAT A.C.), Guanajuato, Mexico. Correo: jbhayet@cimat.mx.

 

Article received on 11/03/2010.
Accepted on 04/02/2011.

 

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.

Keywords: Calibration, computer vision, tracking, video–surveillance and multiple camera systems.

 

Resumen

Este artículo propone un nuevo método robusto para realizar las calibraciones inter–cámaras y suelo–cámara en el contexto de vídeo–vigilancia sobre escenas pobladas por humanos. Suponemos que los agentes transitan en un simple plano y que los parámetros intrínsecos de las cámaras son conocidos. Usamos las trayectorias de objetos en movimiento en las imágenes, como por ejemplo las generadas por algoritmos de rastreo del estado del arte, para estimar los parámetros extrínsecos de las diferentes cámaras. Ilustramos el desempeño de nuestro algoritmo sobre diferentes configuraciones experimentales desafiantes, y lo comparamos con diferentes métodos existentes.

Palabras clave: Calibración de cámaras, visión por computadora, rastreo, vídeo–vigilancia y sistemas de cámaras múltiples.

 

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