Error analysis of photometric stereo with colour lights

Klaudiny, Martin; Hilton, Adrian

doi:10.1016/j.patrec.2013.12.013

Cited by 8 publications

(12 citation statements)

References 17 publications

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“…This paper has presented a thorough analysis of outdoor PS under various illumination conditions captured over the course of a single day. In this scenario, we have no control over illumination, so existing methods for setting up optimal lighting [14], [15] cannot be applied. Through a datadriven analysis of the expected behavior of outdoor PS, we reveal natural factors that distinguish good and unfavorable daylight conditions and identify mainly two different types of working weather conditions: partially cloudy and clear days.…”

Section: Discussionmentioning

confidence: 99%

“…Another important issue is that, so far, most of the literature on PS has adopted a simple directional illumination model, for which optimal lighting configurations can be theoretically derived [13], [14], [15]. Until recently, no attempt had been made to model natural lighting more realistically in an outdoor setup, where lighting cannot be controlled and atmospheric effects are difficult to predict.…”

Section: Related Workmentioning

confidence: 99%

“…To assess the reliability of a solution x, we follow standard practice in PS [15], [33] and consider image measurements corrupted by zero-mean Gaussian noise with equal variance σ 2 (as least squares estimation is only optimal for this practical, most common noise model). Thus, b in eq.…”

Section: Measuring Uncertaintymentioning

confidence: 99%

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Single Day Outdoor Photometric Stereo

Hold-Geoffroy

Gotardo

Lalonde

2021

IEEE Trans. Pattern Anal. Mach. Intell.

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Photometric Stereo (PS) under outdoor illumination remains a challenging, ill-posed problem due to insufficient variability in illumination. Months-long capture sessions are typically used in this setup, with little success on shorter, single-day time intervals. In this paper, we investigate the solution of outdoor PS over a single day, under different weather conditions. First, we investigate the relationship between weather and surface reconstructability in order to understand when natural lighting allows existing PS algorithms to work. Our analysis reveals that partially cloudy days improve the conditioning of the outdoor PS problem while sunny days do not allow the unambiguous recovery of surface normals from photometric cues alone. We demonstrate that calibrated PS algorithms can thus be employed to reconstruct Lambertian surfaces accurately under partially cloudy days. Second, we solve the ambiguity arising in clear days by combining photometric cues with prior knowledge on material properties, local surface geometry and the natural variations in outdoor lighting through a CNN-based, weakly-calibrated PS technique. Given a sequence of outdoor images captured during a single sunny day, our method robustly estimates the scene surface normals with unprecedented quality for the considered scenario. Our approach does not require precise geolocation and significantly outperforms several state-of-the-art methods on images with real lighting, showing that our CNN can combine efficiently learned priors and photometric cues available during a single sunny day.Index Terms-photometric stereo, high dynamic range, deep learning, outdoor lighting !

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Single Day Outdoor Photometric Stereo

Hold-Geoffroy

Gotardo

Lalonde

2021

IEEE Trans. Pattern Anal. Mach. Intell.

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“…However, the 3D reconstruction based on multiple illumination setup requires the accurate control of light intensity and direction (an analysis of the error propagated by inaccuracy is presented in [6]). The reconstructed function L can be considered also a slicing of the material BRDF 3 , allowing in principle to obtain material discrimination from PTM/RTI reconstructions.…”

Section: Reflectance Transformation Imagingmentioning

confidence: 99%

“…Errors in the assumptions regarding the illumination pattern may also create artefacts in the shape detail reconstruction and may affect the correct interpretation of the data. If we want to derive from coefficients of polynomial (PTM) 5 or Spherical Harmonics-based (HSH) 2 fitting multi-light acquisition, intrinsic properties of materials or geometric information (normals that can be used for surface recovery), we should assume to have at each pixel location a correct estimation of light intensity and direction (and also to know if there are shadows or specular highlights) [6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Light calibration and quality assessment methods for Reflectance Transformation Imaging applied to artworks' analysis

et al. 2015

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In this paper we analyze some problems related to the acquisition of multiple illumination images for Polynomial Texture Maps (PTM) or generic Reflectance Transform Imaging (RTI). We show that intensity and directionality nonuniformity can be a relevant issue when acquiring manual sets of images with the standard highlight-based setup both using a flash lamp and a LED light. To maintain a cheap and flexible acquisition setup that can be used on field and by non-experienced users we propose to use a dynamic calibration and correction of the lights based on multiple intensity and direction estimation around the imaged object during the acquisition.Preliminary tests on the results obtained have been performed by acquiring a specifically designed 3D printed pattern in order to see the accuracy of the acquisition obtained both for spatial discrimination of small structures and normal estimation, and on samples of different types of paper in order to evaluate material discrimination.We plan to design and build from our analysis and from the tools developed and under development a set of novel procedures and guidelines that can be used to turn the cheap and common RTI acquisition setup from a simple way to enrich object visualization into a powerful method for extracting quantitative characterization both of surface geometry and of reflective properties of different materials. These results could have relevant applications in the Cultural Heritage domain, in order to recognize different materials used in paintings or investigate the ageing status of artifacts' surface.

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