1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.
The surface normal estimation from photometric stereo becomes less reliable when the surface reflectance deviates from the Lambertian assumption. The non-Lambertian effect can be explicitly addressed by physics modeling to the reflectance function, at the cost of introducing highly nonlinear optimization. This paper proposes a numerical compensation scheme that attempts to minimize the angular error to address the non-Lambertian photometric stereo problem. Due to the multifaceted influence in the modeling of non-Lambertian reflectance in photometric stereo, directly minimizing the angular errors of surface normal is a highly complex problem. We introduce an alternating strategy, in which the estimated reflectance can be temporarily regarded as a known variable, to simplify the formulation of angular error. To reduce the impact of inaccurately estimated reflectance in this simplification, we propose a numerical compensation scheme whose compensation weight is formulated to reflect the reliability of estimated reflectance. Finally, the solution for the proposed numerical compensation scheme is efficiently computed by using cosine difference to approximate the angular difference. The experimental results show that our method can significantly improve the performance of the state-of-the-art methods on both synthetic data and real data with small additive costs. Moreover, our method initialized by results from the baseline method (least-square-based) achieves the state-of-the-art performance on both synthetic data and real data with significantly smaller overall computation, i.e. , about eight times faster compared with the state-of-the-art methods.
© Copyright 2020 IEEE – All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions.
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.