Fast 3D face reconstruction based on uncalibrated photometric stereo

Sun, Yu; Dong, Junyu; Jian, Muwei; Qi, Lin

doi:10.1007/s11042-013-1791-3

Cited by 18 publications

(5 citation statements)

References 26 publications

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“…Sun, et al . 21 combined a lighting calibration method, which uses a reference face model to estimate the lighting parameters from face images taken under unknown illumination, with the classical photometric stereo to reconstruct 3D faces rapidly. Chandraker, et al .…”

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confidence: 99%

A fast 3D reconstruction system with a low-cost camera accessory

Zhang

Gibson

Hay

et al. 2015

Sci Rep

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Photometric stereo is a three dimensional (3D) imaging technique that uses multiple 2D images, obtained from a fixed camera perspective, with different illumination directions. Compared to other 3D imaging methods such as geometry modeling and 3D-scanning, it comes with a number of advantages, such as having a simple and efficient reconstruction routine. In this work, we describe a low-cost accessory to a commercial digital single-lens reflex (DSLR) camera system allowing fast reconstruction of 3D objects using photometric stereo. The accessory consists of four white LED lights fixed to the lens of a commercial DSLR camera and a USB programmable controller board to sequentially control the illumination. 3D images are derived for different objects with varying geometric complexity and results are presented, showing a typical height error of <3 mm for a 50 mm sized object.

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mentioning

confidence: 99%

A fast 3D reconstruction system with a low-cost camera accessory

Zhang

Gibson

Hay

et al. 2015

Sci Rep

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“…The goal of shape from stereo matching-based method (SFSM) is to estimate a high-resolution dense depth map by finding corresponding pixels in image pairs taken simultaneously from different viewpoints [20]. Sun et al [21] proposed a fast framework for 3D face reconstruction by using uncalibrated photometric stereo. With a reference face model, lighting parameters were estimated from input face images lit by unknown illumination, which can be used in classical photometric stereo to estimate the surface normal and albedo.…”

Section: Previous Workmentioning

confidence: 99%

Three-Dimensional Face Reconstruction Using Multi-View-Based Bilinear Model

Tian

Liu

Wei

2019

Sensors

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Face reconstruction is a popular topic in 3D vision system. However, traditional methods often depend on monocular cues, which contain few feature pixels and only use their location information while ignoring a lot of textural information. Furthermore, they are affected by the accuracy of the feature extraction method and occlusion. Here, we propose a novel facial reconstruction framework that accurately extracts the 3D shapes and poses of faces from images captured at multi-views. It extends the traditional method using the monocular bilinear model to the multi-view-based bilinear model by incorporating the feature prior constraint and the texture constraint, which are learned from multi-view images. The feature prior constraint is used as a shape prior to allowing us to estimate accurate 3D facial contours. Furthermore, the texture constraint extracts a high-precision 3D facial shape where traditional methods fail because of their limited number of feature points or the mostly texture-less and texture-repetitive nature of the input images. Meanwhile, it fully explores the implied 3D information of the multi-view images, which also enhances the robustness of the results. Additionally, the proposed method uses only two or more uncalibrated images with an arbitrary baseline, estimating calibration and shape simultaneously. A comparison with the state-of-the-art monocular bilinear model-based method shows that the proposed method has a significantly higher level of accuracy.

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“…J Roth et al [10], proposed a photometric stereo-based approach in which 2D landmarks and basic template are given to the iterative process that reconstruct the surface by estimating the 3D landmarks and photometric normal. Sun Y et al [11] [12], uncalibrated Photometric Stereo approach used, reconstructs 3D face by iteratively estimates the different illumination conditions with the help of face albedo and surface normal.…”

Section: Literature Reviewmentioning

confidence: 99%

The Photometric Stereo Approach and the Visualization of 3D Face Reconstruction

Khan¹,

Ullah²,

Shahid³

et al. 2019

ijacsa

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The 3D Morphable models of the human face have prepared myriad of applications in computer vision, human computer interaction and security surveillances. However, due to the variation in size, complexity of training data set, the landmark mapping, the representation in real time and rendering or synthesis of images in three dimensional is limited. In this paper, we extend the approach of the photometric stereo and provide the human face reconstruction in three dimensional. The proposed method consists of two steps. First it automatically detects the face and segment the iris along with statistical features of pupil location in it. Secondly it provides the selection of minimum six features and where iris process to generate the 3D face. In compare with existing methods our approach provides the automation which produces more better and efficient results in contrast to the manual methods.

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Fast 3D face reconstruction based on uncalibrated photometric stereo

Cited by 18 publications

References 26 publications

A fast 3D reconstruction system with a low-cost camera accessory

A fast 3D reconstruction system with a low-cost camera accessory

Three-Dimensional Face Reconstruction Using Multi-View-Based Bilinear Model

The Photometric Stereo Approach and the Visualization of 3D Face Reconstruction

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