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Application Of Neural Network In Integration Of Shape From Shading And Stereo

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Kumar, Sanjeev (Author)
مؤلفين آخرين: Kumar, Manoj (Co-Author)
المجلد/العدد: مج24, ع2
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2012
الصفحات: 129 - 136
DOI: 10.33948/0584-024-002-005
ISSN: 1319-1578
رقم MD: 972803
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
كلمات المؤلف المفتاحية:
Disparity | Function Approximation | Neural Network | Shape From Shading | Stereo Vision
رابط المحتوى:
صورة الغلاف QR قانون
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المستخلص: In this paper, a simple and efficient approach is presented for the reconstruction of 3-D surfaces using the integration of shape from shading (SfS) and stereo. First, a new SfS algorithm is derived to obtain the depth map of a 3-D surface using linear and generalized Lambertian reflectance model. Later, the accuracy of the depth-map is improved by integrating stereo depth data. The stereo sparse depth data are obtained at the points which have higher similarity score in the rectified pair of stereo images. A feed-forward neural network is used to integrate the SfS and stereo depth data due to its strong nonlinear function approximation property. The integration process is based on the correction of 3-D visible surface obtained from SfS using the stereo data. The experiments have been performed on real and synthetic images to demonstrate the usability and accuracy of the approach.

ISSN: 1319-1578

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