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A Model Deformation Approach for 3D Reconstruction
Yung-Yang Chiang,Min-Liang Wang,Huei-Yung Lin,Pei-Yung Lee,Chin-Chen Chang 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12
In this paper, we present a model deformation approach based on a visual hull technique for improving 3D reconstruction. The proposed approach combines the exquisite 3D model derived by active acquisition methods and the constraints from the rough 3D model derived by passive methods. We take the advantages of active and passive methods to obtain a 3D model with the better quality. The clustering method is adopted to segment 3D models into several sub-models and we then match the sub-models individually via an iterative closest point algorithm. Three testing 3D models are used for evaluating the proposed approach. The results demonstrate the feasibility of the proposed approach.
The simple and easy way to manufacture counter electrode for dye-sensitized solar cells
Jo-Lin Lan,Yung-Yun Wang,Chi-Chao Wan,Tzu-Chien Wei,Hsien-Ping Feng,Chao Peng,Hai-Peng Cheng,Ya-Huei Chang,Wen-Chi Hsu 한국물리학회 2010 Current Applied Physics Vol.10 No.2
We previously developed poly-N-vinyl-2-pyrrolidone (PVP)-capped Pt nanoclusters on ITO glass via a simple ‘‘2-step dip coating process” as counter electrode for DSSC. This new counter electrode was examined by transmission electron microscopy (TEM), inductively coupled plasma-atomic emission spectroscopy (ICP-AES), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and current–voltage curve (I–V curve). The TEM results revealed that PVP-capped Pt nanoclusters’ size is about 3 nm, and the amount of Pt deposited on ITO glass is about 5 ㎍/㎠. Comparing with sputtered Pt and Solaronix thermal cluster Pt-catalyst T/SP, the PVP-capped Pt counter electrode has lower amount of Pt deposited on TCO glass,more positive potential of tri-iodide reduction, and better performance for the charge-transfer resistance (RCT) and the cell efficiency (g).
Face and Gesture Based Human Computer Interaction
Yo-Jen Tu,Chung-Chieh Kao,Huei-Yung Lin,Chin-Chen Chang 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.9
In this paper, we present a face and gesture based human computer interaction (HCI) system. We combine head pose and hand gesture to control the system. We can identify the positions of the eyes and mouth, and use the face center to estimate the pose of the head. Moreover, we introduce a technique for automatic gesture area segmentation and orientation normalization of the hand gesture. The user does not need to keep gestures in upright position and the system segments and normalizes the gestures automatically. The experimental results show that the proposed approach is accurate with gesture recognition rate of 93.6%. Also, the user can control multiple devices, including robots simultaneously through a wireless network.