We proposed a texture mapping technique that comprises mesh partitioning, mesh parameterization and packing, texture transferring, and texture correction and optimization for generating a high-quality texture map of a three-dimensional (3D) model for applications in e-commerce presentations. The main problems in texture mapping are that the texture resolution is generally worse than in the original images and considerable photo inconsistency exists at the transition of different image sources. To improve the texture resolution, we employed an oriented boundary box method for placing mesh islands on the parametric (UV) map. We also provided a texture size that can keep the texture resolution of the 3D textured model similar to that of the object images. To improve the photo inconsistency problem, we employed a method to detect and overcome the missing color that might exist on a texture map. We also proposed a blending process to minimize the transition error caused by different image sources. Thus, a high-quality 3D textured model can be obtained by applying this series of processes for presentations in e-commerce.
The current paper presents a system for the dynamic simulation of the human hand. The simulation of the human hand offers the capability to acquire handshapes that correspond to letters of the finger alphabet, enabling an integrated representation of words and sentences. The hand model is designed using the Autodesk Inventor TM and Autodesk AutoCad TM design environments. The user is able to type words or sentences which are dynamically translated into postures according to the finger alphabet. The system is based on the physiometric characteristics of an average human hand. High precision design is utilized in every part through integration of all the necessary functionalities needed to perform the movements required. The system has been tested on more than 500 words with a letter representation success rate in the range of 95-97%.
The current paper presents a system for the dynamic simulation of the human hand. The simulation of the human hand offers the capability to acquire handshapes that correspond to letters of the finger alphabet, enabling an integrated representation of words and sentences. The hand model is designed using the Autodesk Inventor TM and Autodesk AutoCad TM design environments. The user is able to type words or sentences which are dynamically translated into postures according to the finger alphabet. The system is based on the physiometric characteristics of an average human hand. High precision design is utilized in every part through integration of all the necessary functionalities needed to perform the movements required. The system has been tested on more than 500 words with a letter representation success rate in the range of 95-97%.
While machining width is an important factor of the machining time of freeform surface finishing operations, in reality the kinematic capability of the machine tool is usually the bottleneck of achieving higher feed speed and optimal machining time. The purpose of this paper is to conveniently (and approximately) determine the optimal cut direction considering the speed kinematic capability of the machine tool, without having to compute the actual tool path. We propose a mathematical instrument, called Machine Kinematic Metric (MKM), to easily evaluate infinitesimal machining time on a freeform surface based on machine kinematic consideration. It's a tensor field similar to the metric tensor in differential geometry. MKM is integrated over the part surface to approximate the cut-direction-dependent total machining time, and used to determine the optimal cut direction that minimizes the machining time. To validate the accuracy of the prediction using MKM, we apply the method and compute the machining time at every direction with one degree apart and derive the optimal cut-direction. The computation is performed on two examples: a simple freeform surface and a complex die face model. We then use a commercial CNC emulator software from Huazhong CNC to precisely simulate the machining time in distributed cut directions (five degree apart) for the two models. We find that the optimal cut direction determined from CNC simulation is consistent with the prediction from the proposed method. It validates that the proposed method is a convenient and economical tool to approximately determine the optimal cut direction based on machine speed kinematic capability.
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