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Author |
Ignasi Rius; Jordi Gonzalez; Javier Varona; Xavier Roca |
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Title |
Action-specific motion prior for efficient bayesian 3D human body tracking |
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Journal Article |
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Year |
2009 |
Publication |
Pattern Recognition |
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PR |
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42 |
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11 |
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2907–2921 |
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In this paper, we aim to reconstruct the 3D motion parameters of a human body
model from the known 2D positions of a reduced set of joints in the image plane.
Towards this end, an action-specific motion model is trained from a database of real
motion-captured performances. The learnt motion model is used within a particle
filtering framework as a priori knowledge on human motion. First, our dynamic
model guides the particles according to similar situations previously learnt. Then, the solution space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, we are able to track the 3D configuration of the full human body from several cycles of walking motion sequences using only the 2D positions of a very reduced set of joints from lateral or frontal viewpoints. |
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0031-3203 |
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ISE @ ise @ RGV2009 |
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1159 |
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Author |
Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez |
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Title |
Generation of Augmented Video Sequences Combining Behavioral Animation and Multi Object Tracking |
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Journal Article |
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Year |
2009 |
Publication |
Computer Animation and Virtual Worlds |
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20 |
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4 |
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473–489 |
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In this paper we present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. The resulting framework allows to generate video sequences involving behavior-based virtual agents that react to real agent behavior and has applications in education, simulation, and in the game and movie industries. We show the performance of the proposed approach in an indoor and outdoor scenario simulating human and vehicle agents. Copyright © 2009 John Wiley & Sons, Ltd.
We present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. © 2009 Wiley Periodicals, Inc. |
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ISE @ ise @ BFR2009 |
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1170 |
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Author |
Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez |
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Title |
Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences |
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Year |
2010 |
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EURASIP Journal on Advances in Signal Processing |
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EURASIPJ |
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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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1110-8657 |
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ISE @ ise @ MRR2010 |
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1208 |
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Author |
Jordi Gonzalez; Dani Rowe; Javier Varona; Xavier Roca |
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Title |
Understanding Dynamic Scenes based on Human Sequence Evaluation |
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Journal Article |
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Year |
2009 |
Publication |
Image and Vision Computing |
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IMAVIS |
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27 |
Issue |
10 |
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1433–1444 |
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Image Sequence Evaluation; High-level processing of monitored scenes; Segmentation and tracking in complex scenes; Event recognition in dynamic scenes; Human motion understanding; Human behaviour interpretation; Natural-language text generation; Realistic demonstrators |
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In this paper, a Cognitive Vision System (CVS) is presented, which explains the human behaviour of monitored scenes using natural-language texts. This cognitive analysis of human movements recorded in image sequences is here referred to as Human Sequence Evaluation (HSE) which defines a set of transformation modules involved in the automatic generation of semantic descriptions from pixel values. In essence, the trajectories of human agents are obtained to generate textual interpretations of their motion, and also to infer the conceptual relationships of each agent w.r.t. its environment. For this purpose, a human behaviour model based on Situation Graph Trees (SGTs) is considered, which permits both bottom-up (hypothesis generation) and top-down (hypothesis refinement) analysis of dynamic scenes. The resulting system prototype interprets different kinds of behaviour and reports textual descriptions in multiple languages. |
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ISE @ ise @ GRV2009 |
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1211 |
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Author |
Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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Title |
Generalized Gamut Mapping using Image Derivative Structures for Color Constancy |
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Journal Article |
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Year |
2010 |
Publication |
International Journal of Computer Vision |
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IJCV |
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86 |
Issue |
2-3 |
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127-139 |
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The gamut mapping algorithm is one of the most promising methods to achieve computational color constancy. However, so far, gamut mapping algorithms are restricted to the use of pixel values to estimate the illuminant. Therefore, in this paper, gamut mapping is extended to incorporate the statistical nature of images. It is analytically shown that the proposed gamut mapping framework is able to include any linear filter output. The main focus is on the local n-jet describing the derivative structure of an image. It is shown that derivatives have the advantage over pixel values to be invariant to disturbing effects (i.e. deviations of the diagonal model) such as saturated colors and diffuse light. Further, as the n-jet based gamut mapping has the ability to use more information than pixel values alone, the combination of these algorithms are more stable than the regular gamut mapping algorithm. Different methods of combining are proposed. Based on theoretical and experimental results conducted on large scale data sets of hyperspectral, laboratory and realworld scenes, it can be derived that (1) in case of deviations of the diagonal model, the derivative-based approach outperforms the pixel-based gamut mapping, (2) state-of-the-art algorithms are outperformed by the n-jet based gamut mapping, (3) the combination of the different n-jet based gamut |
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Kluwer Academic Publishers Hingham, MA, USA |
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0920-5691 |
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ISE;CIC |
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CAT @ cat @ GGW2010 |
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1274 |
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