Jorge Azorín López

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Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method(More)
This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of(More)
The automatic understanding of the behaviour conducted by humans in scenarios using images as input of the system is a very important and challenging problem involving different areas of computational intelligence. In this paper human activity recognition is studied from a prediction point of view. We propose a model that, in addition to the capabilities of(More)
Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied(More)
Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC(More)
There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image(More)
In this paper, an architecture for image segmentation and labelling obtained in real conditions is proposed. The model is based on the texture identification of the scene's objects by means of comparison with a database that stores series of each texture perceived with successive optic parameter values: collection of each perceived texture at successive(More)