Jordi Gonzalez, Javier Varona, Xavier Roca, & Juan J. Villanueva. (2001). Human Activity Learning and Recognition from Appearance..
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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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Jordi Gonzalez, Javier Varona, Xavier Roca, & Juan J. Villanueva. (2003). Automatic Keyframing of Human Actions for Computer Animation.
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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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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. (2004). Analysis of Human Walking Based on aSpaces.
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Jordi Gonzalez, Javier Varona, Xavier Roca, & Juan J. Villanueva. (2004). Situation Graph Trees for Human Behavior Modeling.
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Jordi Gonzalez, Javier Varona, Xavier Roca, & Juan J. Villanueva. (2005). A Comparison Framework for Walking Performances using aSpaces. Electronic Letters on Computer Vision and Image Analysis, Special Issue on articulated Motion, 5(3):105–116 (Electronic Letters: IF: 1.016).
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Jordi Gonzalez, Javier Varona, Juan J. Villanueva, & Xavier Roca. (2001). On-line Human Activity Recognition for Video Surveillance..
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Ivan Huerta, Ariel Amato, Jordi Gonzalez, & Juan J. Villanueva. (2008). Fusing Edge Cues to Handle Colour Problems in Image Segmentation. In Articulated Motion and Deformable Objects, 5th International Conference (Vol. 5098, 279–288). LNCS.
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Ivan Huerta, Michael Holte, Thomas B. Moeslund, & Jordi Gonzalez. (2009). Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios. In 12th International Conference on Computer Vision (pp. 1499–1506).
Abstract: Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering “a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions.
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Ivan Huerta, Dani Rowe, Jordi Gonzalez, & Juan J. Villanueva. (2006). Efficient Incorporation of Motionless Foreground Objects for Adaptive Background Segmentation. In IV Conference on Articulated Motion and Deformable Objects (AMDO´06), LNCS 4069: 424–433.
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Ivan Huerta, Dani Rowe, Mikhail Mozerov, & Jordi Gonzalez. (2007). Improving Background Subtraction based on a Casuistry of Colour-Motion Segmentation Problems. In 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:475–482.
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Ivan Huerta. (2007). Image-Sequence Segmentation in Uncontrolled Environments.
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