การสร้างภาพใบหน้าคน 3 มิติ จากภาพหลายมุมมอง - มนัสนันท์ ศรีคำ (จุฬาลงกรณ์มหาวิทยาลัย, 2009)
3D reconstruction is one of the most important techniques in digital image processing. Points in 2D plane are projected into 3D space by using various reconstruction approaches. In the present time, there are two types of 3D face reconstruction, laser scan technique and 2D images. Although 3D face reconstruction using laser scan technique can provide high precision and accuracy, the instruments and installation are very expensive. In contrast, 3D face reconstruction from 2D images provides low cost, but at the same time, it yields low accuracy and precision. Thus, many researches have been devoted to 3D reconstruction from 2D images in order to gain performance as good as we can get from laser scan. This thesis proposed 3D face reconstruction from multiview images by those from 2 parts. First, images are segmented by using active shape models which is obtained from face training data for face image segmentation. An active shape models consist of alignment shape, principle component analysis, and fitting shape models. The second part is 3D face reconstruction using direct linear transformation which is a strategy used to find the camera parameter self-calibrations. The algorithm retains simplicity, and at the same time, it can achieve acceptable results.