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The purpose of this paper is to present a unified approach to uncertainty and sensitivity analysis for camera calibration.

The approach is based on the fact that camera calibration is a problem of parameter estimation and the parameters of interest are given by the optimal solution of a least‐squares problem.

A system of linear equations relating the errors of the extracted feature points to the errors of the estimated parameters is derived, and the expression of the covariance matrix of the estimated parameters is given. Also, a system of linear equations characterizing the influence of the uncalibrated parameters on the calibrated ones is presented. Simulation results show that the camera's position and orientation are less sensitive to the lens distortion than the offset of the image center.

The models developed can be applied to optimize the layout of the calibration marks and design multiple‐stage calibration algorithm. The rationale can also find applications in image registration and robot calibration.

A generic approach is proposed to perform uncertainty and sensitivity analysis for camera calibration. By using the optimality condition for an unconstrained optimization problem, two mathematical models are developed in a unified framework.

The purpose of this paper is to investigate consumer motivations to boutique hotels in Xiamen, China with the push-pull theory.

The survey for this study was conducted in boutique hotels in Xiamen, China.

The results indicated identified “uniqueness-seeking,” “interpersonal experience,” and “social networking” as the primary push motivations and “decoration & theme” and “site value” as the primary pull motivations.

The study is anticipated to provide the industry practitioners in boutique hotels marketing strategies such as positioning, packaging, and advertising.