TY - CHAP

T1 - A fast simultaneous alignment of multiple range images

AU - Oishi, Takeshi

AU - Nakazawa, Atsushi

AU - Kurazume, Ryo

AU - Ikeuchi, Katsushi

PY - 2008

Y1 - 2008

N2 - This chapter describes a fast, simultaneous alignment method for a large number of range images. Generally the most time-consuming task in aligning range images is searching corresponding points. The fastest searching method is the "Inverse Calibration" method. However, this method requires pre-computed lookup tables and precise sensor parameters. We propose a fast searching method using "index images", which work as look-up tables and are rapidly created without any sensor parameters by using graphics hardware. To accelerate the computation to estimate rigid transformations, we employed a linear error evaluation method. When the number of range images increases, the computation time for solving the linear equations becomes too long because of the large size of the coefficient matrix. On the other hand, the coefficient matrix has the characteristic of becoming sparser as the number of range images increases. Thus, we applied the Incomplete Cholesky Conjugate Gradient (ICCG) method to solve the equations and found that the ICCG greatly accelerates the matrix operation by pre-conditioning the coefficient matrix. Some experimental results in which a large number of range images are aligned demonstrate the effectiveness of our method.

AB - This chapter describes a fast, simultaneous alignment method for a large number of range images. Generally the most time-consuming task in aligning range images is searching corresponding points. The fastest searching method is the "Inverse Calibration" method. However, this method requires pre-computed lookup tables and precise sensor parameters. We propose a fast searching method using "index images", which work as look-up tables and are rapidly created without any sensor parameters by using graphics hardware. To accelerate the computation to estimate rigid transformations, we employed a linear error evaluation method. When the number of range images increases, the computation time for solving the linear equations becomes too long because of the large size of the coefficient matrix. On the other hand, the coefficient matrix has the characteristic of becoming sparser as the number of range images increases. Thus, we applied the Incomplete Cholesky Conjugate Gradient (ICCG) method to solve the equations and found that the ICCG greatly accelerates the matrix operation by pre-conditioning the coefficient matrix. Some experimental results in which a large number of range images are aligned demonstrate the effectiveness of our method.

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U2 - 10.1007/978-0-387-75807_6

DO - 10.1007/978-0-387-75807_6

M3 - Chapter

AN - SCOPUS:84891434501

SN - 9780387758060

SP - 89

EP - 107

BT - Digitally Archiving Cultural Objects

PB - Springer US

ER -