|
|
Fadi Dornaika, & Angel Sappa. (2007). Real-time Vehicle Ego-Motion using Stereo Pairs and Particle Filters. In Int. Conf. on Image Analysis and Recognition, (Vol. 4633, 469–480). LNCS.
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2007). SFM for Planar Scenes: a Direct and Robust Approach. In book chapter: Informatics in Control, Automation and Robotics II, Ed. J. Filipe, J. Ferrier, J. Cetto and M. Carvalho, pp. 129–136. (best papers ICINCO 2005).
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2007). Rigid and Non-rigid Face Motion Tracking by Aligning Texture Maps and Stereo 3D Models. PRL - Pattern Recognition Letters, 28(15), 2116–2126.
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2007). Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data. In H. Araujo and J. Jorge A. R. J. Braz (Ed.), Advances in Computer Graphics and Computer Vision, (354–366). Springer Verlag.
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2008). Real Time on Board Stereo Camera Pose through Image Registration. In IEEE Intelligent Vehicles Symposium, (804–809).
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2008). Evaluation of an Appearance-based 3D Face Tracker using Dense 3D Data. Machine Vision and Applications, 427–441.
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2008). Real Time Image Registration for Planar Structure and 3D Sensor Pose Estimation. In Asim Bhatti (Ed.), Stereo Vision (Vol. 18, 299–316).
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2009). Instantaneous 3D motion from image derivatives using the Least Trimmed Square Regression. PRL - Pattern Recognition Letters, 30(5), 535–543.
Abstract: This paper presents a new technique to the instantaneous 3D motion estimation. The main contributions are as follows. First, we show that the 3D camera or scene velocity can be retrieved from image derivatives only assuming that the scene contains a dominant plane. Second, we propose a new robust algorithm that simultaneously provides the Least Trimmed Square solution and the percentage of inliers-the non-contaminated data. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed method. Those experiments show that the new robust approach can outperform classical robust schemes.
|
|
|
|
Fadi Dornaika, & Angel Sappa. (2009). A Featureless and Stochastic Approach to On-board Stereo Vision System Pose. IMAVIS - Image and Vision Computing, 27(9), 1382–1393.
Abstract: This paper presents a direct and stochastic technique for real-time estimation of on-board stereo head’s position and orientation. Unlike existing works which rely on feature extraction either in the image domain or in 3D space, our proposed approach directly estimates the unknown parameters from the stream of stereo pairs’ brightness. The pose parameters are tracked using the particle filtering framework which implicitly enforces the smoothness constraints on the estimated parameters. The proposed technique can be used with a driver assistance applications as well as with augmented reality applications. Extended experiments on urban environments with different road geometries are presented. Comparisons with a 3D data-based approach are presented. Moreover, we provide a performance study aiming at evaluating the accuracy of the proposed approach.
Keywords: On-board stereo vision system; Pose estimation; Featureless approach; Particle filtering; Image warping
|
|
|
|
Ferran Diego, Daniel Ponsa, Joan Serrat, & Antonio Lopez. (2008). Video Alignment for Difference-spotting.
Keywords: video alignment
|
|
|
|
Ferran Diego, Daniel Ponsa, Joan Serrat, & Antonio Lopez. (2009). Video alignment for automotive applications.
Keywords: video alignment
|
|
|
|
Ferran Diego, Daniel Ponsa, Joan Serrat, & Antonio Lopez. (2010). Vehicle geolocalization based on video synchronization. In 13th Annual International Conference on Intelligent Transportation Systems (1511–1516).
Abstract: TC8.6
This paper proposes a novel method for estimating the geospatial localization of a vehicle. I uses as input a georeferenced video sequence recorded by a forward-facing camera attached to the windscreen. The core of the proposed method is an on-line video synchronization which finds out the corresponding frame in the georeferenced video sequence to the one recorded at each time by the camera on a second drive through the same track. Once found the corresponding frame in the georeferenced video sequence, we transfer its geospatial information of this frame. The key advantages of this method are: 1) the increase of the update rate and the geospatial accuracy with regard to a standard low-cost GPS and 2) the ability to localize a vehicle even when a GPS is not available or is not reliable enough, like in certain urban areas. Experimental results for an urban environments are presented, showing an average of relative accuracy of 1.5 meters.
Keywords: video alignment
|
|
|
|
A. Dupuy, Joan Serrat, Jordi Vitria, & J. Pladellorens. (1991). Analysis of gammagraphic images by mathematical morphology. In Pattern Recognition and image Analysis: IV Spanish Symposium of Pattern Recognition and image Analysis, World Scientific Pub..
|
|
|
|
M.A. Garcia, & Angel Sappa. (2004). Efficient Generation of Discontinuity-Preserving Adaptive Triangulations from Range Images. IEEE Trans. on Systems, Man, and Cybernetics (Part B), 34(5):2003–2014 (IF: 1.052).
|
|
|
|
Josep M. Gonfaus, Xavier Boix, Joost Van de Weijer, Andrew Bagdanov, Joan Serrat, & Jordi Gonzalez. (2010). Harmony Potentials for Joint Classification and Segmentation. In 23rd IEEE Conference on Computer Vision and Pattern Recognition (3280–3287).
Abstract: Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales. However, these models do not allow multiple labels to be assigned to a single node. At higher scales in the image, this yields an oversimplified model, since multiple classes can be reasonable expected to appear within one region. This simplified model especially limits the impact that observations at larger scales may have on the CRF model. Neglecting the information at larger scales is undesirable since class-label estimates based on these scales are more reliable than at smaller, noisier scales. To address this problem, we propose a new potential, called harmony potential, which can encode any possible combination of class labels. We propose an effective sampling strategy that renders tractable the underlying optimization problem. Results show that our approach obtains state-of-the-art results on two challenging datasets: Pascal VOC 2009 and MSRC-21.
|
|
