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David Guillamet, B. Moghaddam, & Jordi Vitria. (2003). Modeling High-Order Dependencies in Local Appearance Models.
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David Guillamet, B. Moghaddam, & Jordi Vitria. (2003). Higher-Order Dependencies in Local Appearance Models.
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David Guillamet, & Jordi Vitria. (2003). An Experimental Evaluation of K-nn for Linear Transforms of Positive Data. In In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science. 2652:317–325.
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David Guillamet, & Jordi Vitria. (2003). Evaluation of distance metrics for recognition based on non-negative matrix factorization. PRL - Pattern Recognition Letters, 24(9-10), 1599 –1605.
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Jordi Gonzalez, Javier Varona, Xavier Roca, & Juan J. Villanueva. (2003). Automatic Keyframing of Human Actions for Computer Animation.
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David Guillamet, Jordi Vitria, & B. Shiele. (2003). Introducing a weighted non-negative matrix factorization for image classification. PRL - Pattern Recognition Letters, 24(14), 2447–2454.
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Josep Llados, & Gemma Sanchez. (2003). Symbol Recognition Using Graphs.
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David Lloret, Joan Serrat, Antonio Lopez, & Juan J. Villanueva. (2003). Ultrasound to MR Volume Registration for Brain Sinking Measurement.
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David Masip, & Jordi Vitria. (2003). An Experimental Comparision of Dimensionality Reduction for Face Verification Methods.
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David Masip, & Jordi Vitria. (2003). On the Nearest Neighbor Approach for Gender Recognition.
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Jordi Gonzalez, Javier Varona, Xavier Roca, & Juan J. Villanueva. (2003). A Human Action Comparison Framework for Motion Understanding.
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Jordi Gonzalez, Javier Varona, Xavier Roca, & Juan J. Villanueva. (2003). Human Sequence Evaluation: towards Knowledge-based Scene Interpretations.
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David Lloret, Joan Serrat, Antonio Lopez, & Juan J. Villanueva. (2003). Ultrasound to magnetic resonance volume registration for brain sinking measurement.
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David Masip, & Jordi Vitria. (2003). On the Nearest Neighbor Approach for Gender Recognition.
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Judit Martinez, Eva Costa, P. Herreros, Antonio Lopez, & Juan J. Villanueva. (2003). TV-Screen Quality Inspection by Artificial Vision. In Proceedings SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision (QCAV 2003).
Abstract: A real-time vision system for TV screen quality inspection is introduced. The whole system consists of eight cameras and one processor per camera. It acquires and processes 112 images in 6 seconds. The defects to be inspected can be grouped into four main categories (bubble, line-out, line reduction and landing) although there exists a large variability among each particular type of defect. The complexity of the whole inspection process has been reduced by dividing images into smaller ones and grouping the defects into frequency and intensity relevant ones. Tools such as mathematical morphology, Fourier transform, profile analysis and classification have been used. The performance of the system has been successfully proved against human operators in normal production conditions.
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