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The goal of human-robot motion retargeting is to let a robot follow the movements performed by a human subject. This is traditionally achieved by applying the estimated poses from a human pose tracking system to a robot via explicit joint mapping strategies. In this paper, we present a novel approach that combine the human pose estimation and the motion retarget procedure in a unified generative framework...
The production process of steelmaking-continuous casting is a complex process which is high temperature, continuous, and uncertain. A multi-agent based simulation model is proposed to simulate the complex production process. Firstly, we present a simulation system architecture based on multi-agent technique. Secondly, we present the functional structure of agent and the communication / storage mechanism...
Utilizing dental CAD/CAM system to restore occlusal teeth surface provides us with the possibility of greatly reducing the time to serve patients. Surfaces designed should match the existing jaw articulation and preserve the anatomical characteristics of the generic teeth. In addition, to be suitable for clinical applications, the design process must be highly efficient. In this paper, we describe...
In this paper, we develop a method for learning illumination from a single image, which can benefit illumination-invariant algorithms in computer vision and image-based rendering in graphics. Illumination learning has been widely studied, yet still has some shortcomings such as the restriction of Lambertian surfaces and the prerequisite of known shape or texture. Our method can adaptively learn illumination...
As the key problem of content-based three-dimensional model retrieval, feature extraction methods do not achieve ideal performance at present. Most of past feature extraction methods just utilize the attributes of the model itself. Therefore, it is a promising direction to utilize the categorization information in the process of feature extraction. According to the fact that models in the same category...
Matching vehicles subject to both large pose transformations and extreme illumination variations remains a technically challenging problem in computer vision. In this paper, we develop a new and robust framework toward matching and recognizing vehicles with both highly varying poses and drastically changing illumination conditions. By effectively estimating both pose and illumination conditions, we...
Automatic non-rigid registration of 3D time-varying data is fundamental in many vision and graphics applications such as facial expression analysis, synthesis, and recognition. Despite many research advances in recent years, it still remains to be technically challenging, especially for 3D dynamic, densely-sampled facial data with a large number of degrees of freedom (necessarily used to represent...
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