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Carles Fernandez; Xavier Roca; Jordi Gonzalez |
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Providing Automatic Multilingual Text Generation to Artificial Cognitive Systems |
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2008 |
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ISE |
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ISE @ ise @ FRG2008 |
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1021 |
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Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva |
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Title |
On Tracking Inside Groups |
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Journal Article |
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2010 |
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Machine Vision and Applications |
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MVA |
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21 |
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2 |
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113–127 |
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This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions. |
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Springer-Verlag |
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0932-8092 |
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ISE @ ise @ RGP2010 |
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1158 |
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Author |
Ignasi Rius; Jordi Gonzalez; Javier Varona; Xavier Roca |
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Action-specific motion prior for efficient bayesian 3D human body tracking |
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Journal Article |
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2009 |
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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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Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez |
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Solving the Multi Object Occlusion Problem in a Multiple Camera Tracking System |
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2009 |
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Pattern Recognition and Image Analysis |
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19 |
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1 |
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165-171 |
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An efficient method to overcome adverse effects of occlusion upon object tracking is presented. The method is based on matching paths of objects in time and solves a complex occlusion-caused problem of merging separate segments of the same path. |
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1054-6618 |
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ISE @ ise @ MAR2009a |
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1160 |
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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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2009 |
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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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