An Adaptive Correspondence Algorithm for Modeling Scenes with Strong Interreflections

Abstract

Abstract-Modeling real-world scenes, beyond diffuse objects, plays an important role in computer graphics, virtual reality, and other commercial applications. One active approach is projecting binary patterns in order to obtain correspondence and reconstruct a densely sampled 3D model. In such structured-light systems, determining whether a pixel is directly illuminated by the projector is essential to decoding the patterns. When a scene has abundant indirect light, this process is especially difficult. In this paper, we present a robust pixel classification algorithm for this purpose. Our method correctly establishes the lower and upper bounds of the possible intensity values of an illuminated pixel and of a non-illuminated pixel. Based on the two intervals, our method classifies a pixel by determining whether its intensity is within one interval but not in the other. Our method performs better than standard method due to the fact that it avoids gross errors during decoding process caused by strong interreflections. For the remaining uncertain pixels, we apply an iterative algorithm to reduce the inter-reflection within the scene. Thus, more points can be decoded and reconstructed after each iteration. Moreover, the iterative algorithm is carried out in an adaptive fashion for fast convergence.

Adaptive Binocular Fringe Dynamic Projection Method for High Dynamic Range Measurement

“…Compared with other HDR methods [23,24,25,26,27], ABFDP method extends high dynamic range measurement from monocular fringe projection to binocular fringe projection. The intensity modification mask is calculated without pre-known geometry information.…”

“…Addressing that it is difficult to improve the dynamic range by hardware for the most camera sensors [6], many experts have carried out a series of approaches to solve the HDR measurement problem. The methods can be divided into several categories: multi-exposure method [12,13,14], light intensity adjustment method [15,16], color invariance method [17,18,19], polarization method [20,21,22], adaptive fringe pattern method [23,24,25,26,27], and others [28,29]. Considering that the dark regions and bright regions of the fringe image require different exposure times, multi-exposure method becomes a way for HDR problem [12,13,14].…”

“…The adaptive fringe pattern method is another solution, which computes the optimal illuminations according to the correspondence of camera–projector [23,24,25,26,27]. For the problem of strong internal reflection, Xu and Aliaga developed an adaptive corresponding algorithm [23], which may take hours to inspect an unknown scene. Li and Kofman [24] proposed an adaptive fringe pattern projection method by adapting the maximum input gray level.…”

Projective Parallel Single-Pixel Imaging to Overcome Global Illumination in 3D Structure Light Scanning

“…Several methods are developed to solve 3D reconstruction under global illuminations; these methods include highfrequency projection methods [5], [6], [7], regional projection methods [8], [9], [10], [11], and polarization projection methods [12], [13]. However, these methods are based on specific assumptions that may remain unsatisfied in real applications.…”

Multi-camera systems for navigation of robotic systems and surveillance

“…When surfaces are specular, more than three light directions may be required. In fact, the irradiance equation not only requires that the light sources and camera be distant from the surface, it also neglects inter-reflections, which can be a significant source of the shading observed on object surfaces, e.g., the darkening seen inside concave structures such as grooves and crevasses (Nayar, Ikeuchi, & Kanade, 1991;Y. Xu & Aliaga, 2009).…”