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Francisco Jose Perales, Yuhua Luo, & Juan J. Villanueva. (1991). Un metodo Automatico de Rotoscopia Sin Marcas para el Estudio del Movimiento Humano Basado en un modelo Biomecanico. In Primer Congreso Español de Informatica Grafica (pp. 53–65).
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Marco Pedersoli, Jordi Gonzalez, & Juan J. Villanueva. (2009). High-Speed Human Detection Using a Multiresolution Cascade of Histograms of Oriented Gradients. In 4th Iberian Conference on Pattern Recognition and Image Analysis (Vol. 5524). LNCS. Springer Berlin Heidelberg.
Abstract: This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of the detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a Support Vector Machine (SVM) composed by features at different resolution, from coarse for the first level to fine for the last one.
Considering that the spatial stride of the sliding window search is affected by the HOG features size, unlike previous methods based on Adaboost cascades, we can adopt a spatial stride inversely proportional to the features resolution. This produces that the speed-up of the cascade is not only due to the low number of features that need to be computed in the first levels, but also to the lower number of detection windows that needs to be evaluated.
Experimental results shows that our method permits a detection rate comparable with the state of the art, but at the same time a gain in the speed of the detection search of 10-20 times depending on the cascade configuration.
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A. Pujol, Alex Caralps, & Juan J. Villanueva. (2001). On the suitability of pixel-outlier removal in face recognition..
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A. Pujol, Jose Luis Alba, & Juan J. Villanueva. (2001). Supervised Hausdorff-based measures for face recognition..
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Francisco Javier Orozco, Xavier Roca, & Jordi Gonzalez. (2008). Real-Time Gaze Tracking with Appearance-Based Models. MVAP - Machine Vision Applications, 20(6), 353–364.
Abstract: Psychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movement is fast and and hence difficult to use to obtain a precise and robust tracking. Instead, our
method proposed to describe eyelid and iris movements as continuous variables using appearance-based tracking. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques.Thus,
in the proposed method textures are learned on-line from near frontal images and illumination changes, occlusions and fast movements are managed. The method achieves real-time performance by combining two appearance-based trackers to a
backtracking algorithm for eyelid estimation and another for iris estimation. These contributions represent a significant advance towards a reliable gaze motion description for HCI and expression analysis, where the strength of complementary
methodologies are combined to avoid using high quality images, colour information, texture training, camera settings and other time-consuming processes.
Keywords: Keywords Eyelid and iris tracking, Appearance models, Blinking, Iris saccade, Real-time gaze tracking
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Francisco Javier Orozco, & Jordi Gonzalez. (2008). Confidence Assessment on Eyelid and Eyebrow Expression Recognition. In 2008 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008).
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Francisco Javier Orozco, Jordi Gonzalez, Ignasi Rius, & Xavier Roca. (2007). Hierarchical Eyelid and Face Tracking. In 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:499–506.
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Francisco Javier Orozco, F.A. Garcia, J.L. Arcos, & Jordi Gonzalez. (2007). Spatio-Temporal Reasoning for Reliable Facial Expression Interpretation. In Proceedings of the 5th International Conference on Computer Vision Systems.
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Francisco Javier Orozco, Pau Baiget, Jordi Gonzalez, & Xavier Roca. (2006). Eyelids and Face Tracking in Real-Time.
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Mikhail Mozerov, Ignasi Rius, Xavier Roca, & Jordi Gonzalez. (2010). Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences. EURASIPJ - EURASIP Journal on Advances in Signal Processing, .
Abstract: Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.
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Mikhail Mozerov, Ignasi Rius, Xavier Roca, & Jordi Gonzalez. (2006). 3D Human Motion Sequences Synchronization Using Dense Matching Algorithm. In 28th Annual Symposium of the German Association for Pattern Recognition, LNCS 4174: 485–494, ISBN 978–3–540–44412–1.
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Mikhail Mozerov. (2006). An Effective Stereo Matching Algorithm with Optimal Path Cost Aggregation. In 28th Annual Symposium of the German Association for Pattern Recognition, LNCS 4174: 617–626.
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Mikhail Mozerov, & V. Kober. (2006). Impulse Noise Removal with Gradient Adaptive Neighborhoods. Optical Engineering, 45: 67003.
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Mikhail Mozerov, V. Kober, & I.A. Ovseyevich. (2007). Robust Dynamic Programming Algorithm for Motion Detection and Estimation.
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Mikhail Mozerov, V. Kober, & I.A. Ovseyevich. (2006). A Stereo Matching Algorithm with Global Smoothness Criterion.
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