The out-of-plane shape determination in a generalized fringe projection profilometry is presented. The proposed technique corrects the problems in existing approaches, and it can cope well with the divergent illumination encountered in the generalized profilometry. In addition, the technique can automatically detect the geometric parameters of the experimental setup, which makes the generalized fringe projection profilometry simple and practical. The concept was verified by both computer simulations and actual experiments. The technique can be easily employed for out-of-plane shape measurements with high accuracies.

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Saliency detection has attracted significant attention in the field of computer vision technology over years. At present, more than 100 saliency detection models have been proposed. In this paper, a relatively more detailed classification is proposed. Furthermore, we selected 25 models and evaluated their performance using four public image datasets. We also discussed common problems, such as the influence to model performance by prior information and multiple objects. Finally, we offered future research directions.

It is well known that phase-shifting interferometry suffers from inaccuracy in the presence of phase-shifting errors. We have proved the limitation of using a 4-phase algorithm to reduce the phase-measurement error in the presence of the phase-shifting error. A class of 4 + 1-phase error compensating algorithms is formulated. It is shown that the proposed algorithms can effectively minimize the effects of the constant phase-shifting error and possess a superior performance than existing error-compensating algorithms. The effectiveness of the proposed algorithm is demonstrated by computer simulations and experiments.