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Jaume Amores, & Petia Radeva. (2004). Registration and retrieval of medical images. Application to IVUS.
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Debora Gil. (2002). Regularized Curvature Flow. Computer Vision Centre.
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Olivier Penacchio. (2009). Relative Density of L, M, S photoreceptors in the Human Retina (Vol. 135). Master's thesis, , Bellaterra, Barcelona.
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Antonio Lopez, & Joan Serrat. (1997). Ridge/Valley-like structures: Creases, separatrices and drainage patterns.
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Antonio Lopez, & Joan Serrat. (1998). Ridges and Valleys in Image Analysis.
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Felipe Lumbreras, & Joan Serrat. (1996). Segmentation of petrographical image of marbles.
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S. Casanovas. (2000). Seguiment de moviment articulat mitjançant flux òptic i metodes estocastics.
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J.M. Sanchez. (1999). Semantic retrieval from digital video libraries in the TV commercials domain.
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Oriol Martinez. (2004). Semantic Retrieval of Memory Color Content.
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Josep M. Gonfaus. (2009). Semantic Segmentation of Images Using Random Ferns (Vol. 132). Master's thesis, , Bellaterra, Barcelona.
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Raul Chaves. (2004). Sistema de identificacion mediante huellas dactilares.
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D. Smith. (1999). Solving the mean string problem for 2D shapes.
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Miquel Ferrer. (2006). Spectral Median Graphs and its Application to Graphical Symbol Recognition.
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Joel Barajas. (2007). Spectral Rigid Registration of Medical Images: Application to Tagged MRI and IVUS.
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Daniel Hernandez, Alejandro Chacon, Antonio Espinosa, David Vazquez, Juan Carlos Moure, & Antonio Lopez. (2016). Stereo Matching using SGM on the GPU.
Abstract: Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method.
Keywords: CUDA; Stereo; Autonomous Vehicle
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