Existing face recognition systems are based on 2D facial images and exhibit well-known deficiencies. Accordingly, the face recognition research is gradually shifting from classical 2D to sophisticated 3D or hybrid 2D/3D. 3D shape reconstruction from multiview photographs and video sequences (2D images) is an active area of research which can fully leverage the potential of existing 2D image acq...

The 3D Morphable Model (3DMM) and the Structure from Motion (SfM) methods are widely used for 3D facial reconstruction from 2D single-view or multiple-view images. However, model-based methods suffer from disadvantages such as high computational costs and vulnerability to local minima and head pose variations. The SfM-based methods require multiple facial images in various poses. To overcome th...

We examine the utility of Structure from Motion (SfM) point cloud products to generate a digital terrain model (DTM) and estimate canopy heights in a woodland ecosystem in the Texas Hill Country, USA. Very high spatial resolution images were acquired with a Canon PowerShot A800 digital camera mounted on an unmanned aerial system. Image mosaicking and dense point matching were accomplished using...

To evaluate the influence of egomotion on the three-dimensional visual processing of structure-from-motion (SFM), we compared the visual discrimination between planar and spherical surfaces during subject-translation, object-translation, or rotation of the object in depth. Performance was the best for object-rotation, intermediate for subject-translation, and the poorest for object-translation-...

Structure-from-motion (SfM) is an important computer vision problem and largely relies on the quality of feature tracking. In image sequences, if disjointed tracks caused by objects moving in and out of the view, occasional occlusion, or image noise, are not handled well, the corresponding SfM could be significantly affected. In this paper, we address the non-consecutive feature point tracking ...

The regenerative potential of mesenchymal stromal cells (MSC) holds great promise in using them for treatment of a wide range of debilitating diseases. Several types of culture media and systems have been used for large-scale expansion of MSCs in vitro; however, the majority of them rely heavily on using foetal bovine serum (FBS)-supplement for optimal cell proliferation. FBS-based cultures pos...

Many monocular visual SLAM algorithms are derived from incremental structure-from-motion (SfM) methods. This work proposes a novel monocular SLAM method which integrates recent advances made in global SfM. In particular, we present two main contributions to visual SLAM. First, we solve the visual odometry problem by a novel rank1 matrix factorization technique which is more robust to the errors...

In this study, we propose an environment structuring framework to facilitate suitable prior density preparation for MAP-based stochastic feature matching (SFM) for robust speech recognition. We use a two-stage hierarchical structure to construct the environment structuring framework to characterize the regional information of various speaker and speaking environments. With the regional informat...

Submodular function minimization (SFM) is a fundamental and efficiently solvable problem class in combinatorial optimization with a multitude of applications in various fields. Surprisingly, there is only very little known about constraint types under which SFM remains efficiently solvable. The arguably most relevant non-trivial constraint class for which polynomial SFM algorithms are known are...

method is robust enough to be used in industry and society. Stereo is a useful technique for obtaining depth information from images. However, it is required that the baseline length between two cameras should be large to increase depth precision. Consequently, stereo matching suffers from ambiguities due to large baseline length. Therefore, the matching problem would become much easier if a se...