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A one-dimensional calibration object consists of three or more collinear points with known relative positions. It is generally believed that a camera can be calibrated only when a 1D calibration object is in planar motion or rotates around a ¯ xed point. In this paper, it is proved that when a multi-camera is observing a 1D object undergoing general rigid motions synchronously, the camera set can be linearly calibrated. A linear algorithm for the camera set calibration is proposed，and then the linear estimation is further re¯ ned using the maximum likelihood criteria. The simulated and real image experiments show that the proposed algorithm is valid and robust.-A one-dimensional calibration object con sists of three or more points with Conic kno wn relative positions. It is generally believe d that a camera can be calibrated only when a 1D ca libration object is in planar motion or rotates around a

During the past four years, most of our research activities have been focused on image but also video and 3-D objects processing for security applications (watermarking and biometrics) and communications (talking heads, interfaces), with a special emphasis on facial images. More about our work can be found at http://www.eurecom.fr/~image. Our research activities are conducted with the backing of several industrials, in particular France Telecom Research and STMicroelectronics. For the past few years, we have had a regular scientific collaboration on Fractal Image Coding, Watermarking and Biometrics with the University of California, Santa Barbara (UCSB), in particular with Prof. K. Ros

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