Dynamic 3D phase-shifting profilometry based on a corner optical flow algorithm.

Real-time 3D reconstruction has been applied in many fields, calling for many ongoing efforts to improve the speed and accuracy of the used algorithms. Phase shifting profilometry based on the Lucas-Kanade optical flow method is a fast and highly precise method to construct and display the three-dimensional shape of objects. However, in this method, a dense optical flow calculation is required for the modulation image corresponding to the acquired deformed fringe pattern, which consumes a lot of time and affects the real-time performance of 3D reconstruction and display. Therefore, this paper proposes a dynamic 3D phase shifting profilometry based on a corner optical flow algorithm to mitigate this issue. Therein, the Harris corner algorithm is utilized to locate the feature points of the measured object, so that the optical flow needs to calculate for only the feature points which, greatly reduces the amount of calculation time. Both our experiments and simulations show that our method improves the efficiency of pixel matching by four times and 3D reconstruction by two times.

Fast 3D measurement based on improved optical flow for dynamic objects.

High resolution, real-time three-dimensional (3D) measurement plays an important role in many fields. In this paper, a multi-directional dynamic real-time phase measurement profilometry based on improved optical flow is proposed. In a five-step phase shifting dynamic measurement, pixel matching is needed to make the pixels one-to-one corresponding in five patterns. However, in the frequently-used pixel matching method at present, it is necessary to calculate the correlation and traverse the whole deformed pattern for the motion information of the measured object. The huge amount of computation caused by correlation computation takes up most of the time in the process of the entire 3D reconstruction, so it can not meet the requirement of real-time dynamic measurement. In order to solve the problem, the improved optical flow algorithm is introduced to replace correlation calculation in pixel matching. In one measurement, five captured patterns need to be dealt with, and the optical flow between each two adjacent frames is calculated. Then four two-dimensional vector matrices can be obtained. The vector matrices contain the complete motion information of the measured object. Experiments and simulations prove that this method can improve the efficiency of pixel matching by 42 times and 3D reconstruction by 32 times on the premise of ensuring the accuracy.

Dynamic phase measuring profilometry for rigid objects based on simulated annealing.

This paper presents a dynamic phase measurement profilometry (PMP) method based on the simulated annealing algorithm. In dynamic PMP for rigid objects, pixel matching is an effective method to make one-to-one pixel correspondence in each captured pattern. However, pixel matching by the global traversing algorithm takes up most of the time in the whole reconstruction process. For the purpose of optimizing pixel matching and enhancing performance in dynamic PMP, the simulated annealing algorithm is introduced. By generating a random path based on the simulated annealing algorithm, it is sufficient to locate the approximate area of the measured object. Then the accurate position can be calculated by combining it with a partial traversing algorithm. The proposed method can reduce pixel matching time by 63% and increase reconstruction efficiency by 58%. Simulations and experiments prove feasibility and precision.