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Titlebook: Computer Vision - ACCV 2006; 7th Asian Conference P. J. Narayanan,Shree K. Nayar,Heung-Yeung Shum Conference proceedings 2006 Springer-Verl

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The Design of an Extendible Graph Editorghting condition and small individuality. The residual represents individuality and the other information including small noise. The two components complement each other and they are evaluated independently in the framework of eigenface method. The image decomposition can also collaborate with parallel partial projections for robust recognition.
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Gaussian Decomposition for Robust Face Recognitionghting condition and small individuality. The residual represents individuality and the other information including small noise. The two components complement each other and they are evaluated independently in the framework of eigenface method. The image decomposition can also collaborate with parallel partial projections for robust recognition.
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Recommendations And Future Research this, we are concerned with global optimization in order to get a guaranteed solution, with the shortest response time. Interval analysis provides an efficient numerical framework, that reveals to be highly performant, with regard to both estimation accuracy and time-consuming.
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https://doi.org/10.1007/978-3-7908-1978-6of the model parameters while retains most of the original variability, and thus avoids overflowing and weakens the constraints on observations in conventional HMMs. The experimental results proved that the modified HMMs are effective solutions for multi-people interactive activity recognition.
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https://doi.org/10.1007/978-3-7908-1978-6te that the proposed approach is efficient, invariant to linear transformations and capable of learning. To substantiate the success of the proposed model, a comparative study is performed with Murase and Nayar approach.
发表于 2025-3-26 09:58:24 | 显示全部楼层
On Using Silhouettes for Camera Calibrationield is first to establish the exact constraint that camera parameters should satisfy with respect to silhouettes, and second to derive from this constraint new practical criteria to evaluate and to optimize camera parameters. Results on both synthetic and real data illustrate the interest of the proposed framework.
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Towards a Guaranteed Solution to Plane-Based Self-calibration this, we are concerned with global optimization in order to get a guaranteed solution, with the shortest response time. Interval analysis provides an efficient numerical framework, that reveals to be highly performant, with regard to both estimation accuracy and time-consuming.
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