• The KIPS Transactions:PartB
• /
• v.17B no.3
• /
• pp.183-188
• /
• 2010

A factorization-based 3D reconstruction system is realized to recover 3D scene from an image sequence. The image sequence is captured from uncalibrated perspective camera from several views. Many matched feature points over all images are obtained by feature tracking method. Then, these data are supplied to the 3D reconstruction module to obtain the projective reconstruction. Projective reconstruction is converted to Euclidean reconstruction by enforcing several metric constraints. After many triangular meshes are obtained, realistic reconstruction of 3D models are finished by texture mapping. The developed system is implemented in C++, and Qt library is used to implement the system user interface. OpenGL graphics library is used to realize the texture mapping routine and the model visualization program. Experimental results using synthetic and real image data are included to demonstrate the effectiveness of the developed system.

• Korean Journal of Optics and Photonics
• /
• v.19 no.4
• /
• pp.270-275
• /
• 2008

This paper addresses occluded object reconstruction and recognition with computational integral imaging (II). Integral imaging acquires and reconstructs target information in the three-dimensional (3D) space. The reconstruction is performed by averaging the intensities of the corresponding pixels. The distance to the object is estimated by minimizing the sum of the standard deviation of the pixels. We adopt principal component analysis (PCA) to classify occluded objects in the reconstruction space. The Euclidean distance is employed as a metric for decision making. Experimental and simulation results show that occluded targets are successfully classified by the proposed method.

• International Journal of Contents
• /
• v.11 no.2
• /
• pp.9-14
• /
• 2015

We propose a new distance measure between 2-dimensional points to provide a total order for an entire point set and to reflect the correct geometric meaning of the naturalness of the point ordering. In general, there is no total order for 2-dimensional point sets, so curve reconstruction algorithms do not solve the self-intersection problem because the distance used in the previous methods is the Euclidean distance. A natural distance based on Brownian motion was previously proposed to solve the self-intersection problem. However, the distance reflects the wrong geometric meaning of the naturalness. In this paper, we correct the disadvantage of the natural distance by introducing a polar-natural distance, and we also propose a new curve reconstruction algorithm that is based on the polar-natural distance. Our experiments show that the new distance adequately reflects the correct geometric meaning, so non-simple curve reconstruction can be solved.

• Journal of Information Processing Systems
• /
• v.15 no.2
• /
• pp.399-409
• /
• 2019

Three-dimensional (3D) human pose reconstruction from single-view image is a difficult and challenging topic. Existing approaches mostly process frame-by-frame independently while inter-frames are highly correlated in a sequence. In contrast, we introduce a novel spatial-temporal 3D human pose reconstruction framework that leverages both intra and inter-frame relationships in consecutive 2D pose sequences. Orthogonal matching pursuit (OMP) algorithm, pre-trained pose-angle limits and temporal models have been implemented. Several quantitative comparisons between our proposed framework and recent works have been studied on CMU motion capture dataset and Vietnamese traditional dance sequences. Our framework outperforms others by 10% lower of Euclidean reconstruction error and more robust against Gaussian noise. Additionally, it is also important to mention that our reconstructed 3D pose sequences are more natural and smoother than others.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.9
• /
• pp.2016-2022
• /
• 2010

We propose a new algorithm for reconstructing curves with self-intersections from sample points. In general, the result of curve reconstruction depends on how to select and order the representative points to resemble the shape of sample points. Most of the previous point ordering approaches utilize the Euclidean distance to compute the proximity of sample points without directional information, so they can not solve the non-simple curve reconstruction problem. In this paper, we develop a new distance estimating the adjacency between sample points, which is derived from the standard normal distribution of Brownian motion. Experimental results show that this approach is very effective to non-simple curve reconstruction.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.11
• /
• pp.1159-1167
• /
• 2011

A novel 3D tube scanning technique is proposed. The proposed tube scanning technique is developed for a special tube inspection module which consists of four line-lasers and one camera. Using the scanning module, we can reconstruct the 360 degree shapes of the inner surfaces of a cylindrical tube. From an image frame captured by the camera, we reconstruct a partial tube model based on four laser triangulations. Then by aligning such partial models with respect to a reference tube axis, a complete 3D shape of the tube is reconstructed. The tube axis in each reconstructed frame is aligned with a 3D Euclidean transformation to the reference axis. Several experiments show that the proposed method can align multiple tube axes very accurately and reconstruct 3D shapes of a tube with very low shape distortion.

• Maxillofacial Plastic and Reconstructive Surgery
• /
• v.42
• /
• pp.37.1-37.13
• /
• 2020

Background: The human mandible is variable in shape, size and position and any deviation from normal can affect the facial appearance and dental occlusion. Objectives: The objectives of this study were to determine whether the Sassouni cephalometric analysis could help predict two-dimensional mandibular shape in humans using cephalometric planes and landmarks. Materials and methods: A retrospective computerised analysis of 100 lateral cephalometric radiographs taken at Kingston Hospital Orthodontic Department was carried out. Results: Results showed that the Euclidean straight-line mean difference between the estimated position of gonion and traced position of gonion was 7.89 mm and the Euclidean straight-line mean difference between the estimated position of pogonion and the traced position of pogonion was 11.15 mm. The length of the anterior cranial base as measured by sella-nasion was positively correlated with the length of the mandibular body gonion-menton, r = 0.381 and regression analysis showed the length of the anterior cranial base sella-nasion could be predictive of the length of the mandibular body gonion-menton by the equation 22.65 + 0.5426x, where x = length of the anterior cranial base (SN). There was a significant association with convex shaped palates and oblique shaped mandibles, p = 0.0004. Conclusions: The method described in this study can be used to help estimate the position of cephalometric points gonion and pogonion and thereby sagittal mandibular length. This method is more accurate in skeletal class I cases and therefore has potential applications in craniofacial anthropology and the 'missing mandible' problem in forensic and archaeological reconstruction.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.11
• /
• pp.1637-1643
• /
• 2022

In recent years, the demand for image-processing technology in digital marketing has increased due to the expansion and diversification of the digital market, such as video, security, and machine intelligence. Noise-processing is essential for image-correction and reconstruction, especially in the case of sensitive noises, such as in CT, MRI, X-ray, and scanners. The two main salt and pepper noises have been actively studied, but the details and edges are still unsatisfactory and tend to blur when there is a lot of noise. Therefore, this paper proposes an algorithm that applies a weight-based Euclidean distance equation to the partial mask and uses only the non-noisy pixels that are the most similar to the original as effective pixels. The proposed algorithm determines the type of filter based on the state of the internal pixels of the designed partial mask and the degree of mask deterioration, which results in superior noise cancellation even in highly damaged environments.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.2 s.302
• /
• pp.113-120
• /
• 2005

3D reconstruction of a scene structure from un-calibrated image sequences has been long one of the central problems in computer vision. For 3D reconstruction in Euclidean space, projective reconstruction, which is classified into the merging method and the factorization, is needed as a preceding step. By calculating all camera projection matrices and structures at the same time, the factorization method suffers less from dia and error accumulation than the merging. However, the factorization is hard to analyze precisely long sequences because it is based on the assumption that all correspondences must remain in all views from the first frame to the last. This paper presents a new projective reconstruction method for recovery of 3D structure over long sequences. We break a full sequence into sub-sequences based on a quantitative measure considering the number of matching points between frames, the homography error, and the distribution of matching points on the frame. All of the projective reconstructions of sub-sequences are registered into the same coordinate frame for a complete description of the scene. no experimental results showed that the proposed method can recover more precise 3D structure than the merging method.

• Journal of Digital Convergence
• /
• v.13 no.10
• /
• pp.287-293
• /
• 2015

This study proposed signal processing techniques and neural network with weighted fuzzy membership functions(NEWFM) to detect epileptic seizure from EEG signals. This study used wavelet transform(WT), sequential increment method, and phase space reconstruction(PSR) as signal processing techniques. In the first step of signal processing techniques, wavelet coefficients were extracted from EEG signals using the WT. In the second step, sequential increment method was used to extract peaks from the wavelet coefficients. In the third step, 3D diagram was produced from the extracted peaks using the PSR. The Euclidean distances and statistical methods were used to extract 16 features used as inputs for NEWFM. The proposed methodology shows that accuracy, specificity, and sensitivity are 97.5%, 100%, 95% with 16 features, respectively.