Jaechang Shim

Curvature based human face recognition using depth weighted Hausdorff distance

In this paper, we propose a novel implementation of a person verification system based on depth-weighted Hausdorff distance (DWHD) using the surface curvatures of the human face. This new method incorporates the depth information and curvatures of local facial features. The weighting function used in this paper is based on depth values, which have differential properties of a face according to the people, so that the distance of this extracted edge maps are emphasized. Experimental results based on the combination of the maximum, minimum, and Gaussian curvature according to threshold values show that DWHD achieves recognition rate of 92.8%, 97.6% and 92.8% of the cases for 5 ranked candidates, respectively, and the proposed method of combined recognition rate for each curvature shows the best.

3D facial image recognition using a nose volume and curvature based eigenface

The depth information in the face represents personal features in detail. In this study, the important personal facial information was presented by the surface curvatures and the features of vertical and horizontal of nose volume extracted from the face. The approach works by the depth of nose, the area of nose and the volume of nose based both on a vertical and horizontal are calculated. And the principal components analysis (PCA), which is calculated using the curvature data, was presented different features for each person. To classify the faces, the cascade architectures of fuzzy neural networks (CAFNNs), which can guarantee a high recognition rate as well as parsimonious knowledge base, are considered. In the experimental results, 3D images demonstrate the effectiveness of the proposed methods.

An automated facial pose estimation using surface curvature and tetrahedral structure of a nose

This paper introduces an automated 3D face pose estimation method using the tetrahedral structure of a nose. This method is based on the feature points extracted from a face surface using curvature descriptors. A nose is the most protruding component in a 3D face image. A nose shape that is composed of the feature points such as a nasion, nose tip, nose base, and nose lobes, and is similar to a tetrahedron. Face pose can be estimated by fitting the tetrahedron to the coordinate axes. Each feature point can be localized by curvature descriptors. This method can be established using nasion, nose tip, and nose base. It can be applied to face tracking and face recognition.

A Wireless Temperature Control System based on FPGA

In this paper, we designed and built a wired temperature controller system which is based on ASIC for a wireless temperature controller system based on FPGA. FPGA devices and wireless controller systems are growing quickly especially for industrial systems for sensing temperature and humidity. FPGA can set up a desired system and a CPU, and directly set up or change a peripheral device based on an IP quickly for an affordable price. This wireless system is easy to install in the field where there are lots of changes and the system is complex. It also has advantages for maintenance. In this study, we are using a 32 bit RISC CPU based on MicroBlaze, with a touch interface, peripheral device, and porting the embedded Linux. Also, we added wireless communication using ZigBee. With this system we provide remote monitoring and control through the web by adding a web server. Compared to the original system, we say not only a performance improvement, but also more efficient development and cheaper costs. In this study, we focused especially on building a better development environment and a more effective user interface.