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David Guillamet. (1999). Reconeixement d´objectes en entorns poc controlats mitjançant metodes estadistics.
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David Guillamet. (2001). Color histogram classification using NMF.
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David Geronimo. (2006). Model Features and Horizon Line Estimation for Pedestrian Detection in Advanced Driver Assistance Systems. Master's thesis, , .
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David Fernandez. (2010). Handwritten Word Spotting in Old Manuscript Images using Shape Descriptors (Vol. 161). Master's thesis, , .
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David Augusto Rojas. (2009). Colouring Local Feature Detection for Matching (Vol. 133). Master's thesis, , Bellaterra, Barcelona.
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David Aldavert. (2006). Visual Simultaneous Localization and Mapping.
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David Alcalde. (2003). Image classification in terms of rotation-invariant pattern matching.
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Daniel Ponsa. (2001). A model based pedestrian tracking review.
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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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Dani Rowe. (2005). Probabilistic Image-based Tracking in Complex Human Environments.
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Dani Rowe. (2007). Towards Robust Multiple-People Tracking in Unconstrained Environments.
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D. Smith. (1999). Solving the mean string problem for 2D shapes.
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Cristina Cañero, & Petia Radeva. (2002). Predictive (un)distortion model for 3D reconstruction purpouses.
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Cristina Cañero. (1999). Deformable models applied in Medical Imaging.
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Cristhian A. Aguilera-Carrasco. (2014). Evaluation of feature detectors and descriptors in VISIBLE-LWIR cross-spectral imaging (Vol. 177). Master's thesis, , .
Abstract: This thesis evaluates the performance of different state-of-art feature detectors and descriptors algorithms in the Visible-LWIR cross-spectral scenario. The focus is to determine if current detector and descriptor algorithms can be used to match features between the LWIR spectrum and the visible spectrum in applications such as, visual odometry, object recognition, image registration and stereo vision. An outdoor cross-spectral dataset was created to evaluate the suitability of the different algorithms. The results
show that the tested algorithms are not suitable to the task of matching features across different spectra. The repeatability ratio was smaller than the 30 percent in the best case and in general matched features were not accurate located. Additionally, these results also suggest that is necessary to create new algorithms that take into account the nature of the different spectra, describing characteristics that exist in both spectra such as discontinuities.
Keywords: Multi-spectral; Cross-spectral; Visible-LWIR imaging; Multimodal.
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