Inexpensive construction of a 3D face model from stereo images

Hossain, M. Shahriar; Akbar, Memen; Starkey, John

doi:10.1109/iccitechn.2007.4579387

Cited by 4 publications

(4 citation statements)

References 16 publications

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“…However, their method required to project a set of structure lights to form up a grid on the face directly, which was not userfriendly enough. The method presented by Hossain et al (Hossain et al 2007) utilized the stereo vision for 3D facial reconstruction. However, a man-made rectangular board is required behind the user's head, and four corners of this rectangle should be hand-coded with a red color before the process of stereo matching.…”

Section: Related Workmentioning

confidence: 99%

Dense 3D facial reconstruction from a single depth image in unconstrained environment

Shu

Wang

et al. 2017

Virtual Reality

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With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step for those virtual reality tasks. Due to information provided by an additional dimension, 3D facial reconstruction enables aforementioned tasks to be achieved with higher accuracy than those based on 2D facial analysis. The denser the 3D facial model is, the more information it could provide. However, most existing dense 3D facial reconstruction methods require complicated processing and high system cost. To this end, this paper presents a novel method that simplifies the process of dense 3D facial reconstruction by employing only one frame of depth data obtained with an off-the-shelf RGB-D sensor. The experiments showed competitive results with real world data.

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Section: Related Workmentioning

confidence: 99%

Dense 3D facial reconstruction from a single depth image in unconstrained environment

Shu

Wang

et al. 2017

Virtual Reality

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“…There is a range of methods that can reconstruct 3D human faces. However most of them either require complicated and special setup, or come up with low accuracy results [2][3][4][5]. Jo et al [6] presented a 3D face reconstruction method.…”

Section: B Related Workmentioning

confidence: 99%

Automatic Reconstruction of Dense 3D Face Point Cloud with a Single Depth Image

Shu

Yu²,

Dong

et al. 2015

2015 IEEE International Conference on Systems, Man, and Cybernetics

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Human face analysis is the basis for many other computer vision tasks, such as camera surveillance, entrance authorization and age estimation. With 3D face models, the vision task based on facial analysis can usually achieve a higher accuracy than the 2D cases since it provides more information with the additional dimension. However, most existing 3D face reconstruction methods suffer from complicated processing and high computation. This paper presents a novel method that simplifies the 3D face reconstruction process with only one shot of Kinect data. The output of the system is a high density of 3D face point cloud with smoother surface. This provides rich details of the human face for other computer vision tasks. Experiments with real world data show promising results using the proposed method.

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“…A combination of the EM algorithm and a 3D face shape model was suggested in [8] and [9] to accommodate additional poses. To determine the surface characteristics, methods using stereo images were proposed in [10] and [11]. The stereo vision method infers information regarding a 3D structure and the distance of a scene from two or more images taken from two or more cameras from various viewpoints.…”

Section: Introductionmentioning

confidence: 99%

“…The stereo vision method infers information regarding a 3D structure and the distance of a scene from two or more images taken from two or more cameras from various viewpoints. In [10] and [11], it is necessary to first find the correspondences of each image pixel from the different cameras. A 3D structure is then built from these correspondences.…”

Section: Introductionmentioning

confidence: 99%

Rapid Implementation of 3D Facial Reconstruction from a Single Image on an Android Mobile Device

Truong¹,

Park²,

Lee³

et al. 2014

KSII TIIS

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In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.

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Inexpensive construction of a 3D face model from stereo images

Cited by 4 publications

References 16 publications

Dense 3D facial reconstruction from a single depth image in unconstrained environment

Dense 3D facial reconstruction from a single depth image in unconstrained environment

Automatic Reconstruction of Dense 3D Face Point Cloud with a Single Depth Image

Rapid Implementation of 3D Facial Reconstruction from a Single Image on an Android Mobile Device

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