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Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez; N. Paragios |
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Title |
Image Contextual Representation and Matching through Hierarchies and Higher Order Graphs |
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Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
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2664 - 2667 |
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Abstract |
We present a region matching algorithm which establishes correspondences between regions from two segmented images. An abstract graph-based representation conceals the image in a hierarchical graph, exploiting the scene properties at two levels. First, the similarity and spatial consistency of the image semantic objects is encoded in a graph of commute times. Second, the cluttered regions of the semantic objects are represented with a shape descriptor. Many-to-many matching of regions is specially challenging due to the instability of the segmentation under slight image changes, and we explicitly handle it through high order potentials. We demonstrate the matching approach applied to images of world famous buildings, captured under different conditions, showing the robustness of our method to large variations in illumination and viewpoint. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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ADAS |
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no |
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Admin @ si @ RSL2012a; |
Serial |
2032 |
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Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Monocular Egomotion Estimation based on Image Matching |
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Conference Article |
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Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
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Pages |
425-430 |
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SLAM |
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Portugal |
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ICPRAM |
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ADAS |
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no |
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Admin @ si @ CPL2012a;; ADAS @ adas @ |
Serial |
2011 |
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Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Monocular Depth-based Background Estimation |
Type |
Conference Article |
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Year |
2012 |
Publication |
7th International Conference on Computer Vision Theory and Applications |
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Pages |
323-328 |
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In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences. |
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Address |
Roma |
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VISAPP |
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ADAS |
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no |
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Call Number |
Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e |
Serial |
2012 |
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Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Pedestrian Candidates Generation using Monocular Cues |
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Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
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7-12 |
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Keywords |
pedestrian detection |
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Abstract |
Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached. |
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IEEE Xplore |
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ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
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Conference |
IV |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d |
Serial |
2013 |
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Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
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Title |
Planar-Based Multispectral Stereo |
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Conference Article |
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Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
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Naples, Italy |
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QIRT |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ BLA2012 |
Serial |
2016 |
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Author |
Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo |
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Title |
A Novel SIFT-Like-Based Approach for FIR-VS Images Registration |
Type |
Conference Article |
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Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
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Naples, Italy |
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QIRT |
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Notes |
ADAS; TV |
Approved |
no |
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Call Number |
Admin @ si @ ABS2012 |
Serial |
2017 |
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Permanent link to this record |
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Author |
Monica Piñol; Angel Sappa; Angeles Lopez; Ricardo Toledo |
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Title |
Feature Selection Based on Reinforcement Learning for Object Recognition |
Type |
Conference Article |
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Year |
2012 |
Publication |
Adaptive Learning Agents Workshop |
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Pages |
33-39 |
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Address |
Valencia |
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ALA |
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Notes |
ADAS; RV |
Approved |
no |
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Call Number |
Admin @ si @ PSL2012 |
Serial |
2018 |
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Permanent link to this record |
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Author |
German Ros; Angel Sappa; Daniel Ponsa; Antonio Lopez |
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Title |
Visual SLAM for Driverless Cars: A Brief Survey |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles |
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SLAM |
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Address |
Alcalá de Henares |
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IVW |
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ADAS |
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no |
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Admin @ si @ RSP2012; ADAS @ adas |
Serial |
2019 |
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Permanent link to this record |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
An Empirical Study on Optical Flow Accuracy Depending on Vehicle Speed |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
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Pages |
1138-1143 |
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Abstract |
Driver assistance and safety systems are getting attention nowadays towards automatic navigation and safety. Optical flow as a motion estimation technique has got major roll in making these systems a reality. Towards this, in the current paper, the suitability of polar representation for optical flow estimation in such systems is demonstrated. Furthermore, the influence of individual regularization terms on the accuracy of optical flow on image sequences of different speeds is empirically evaluated. Also a new synthetic dataset of image sequences with different speeds is generated along with the ground-truth optical flow. |
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Address |
Alcalá de Henares |
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IEEE Xplore |
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ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
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IV |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ NaS2012 |
Serial |
2020 |
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Author |
Miguel Oliveira; Angel Sappa; V. Santos |
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Title |
Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models |
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Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
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Pages |
299-303 |
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Abstract |
The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
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Address |
Alcalá de Henares |
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Publisher |
IEEE Xplore |
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ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
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Conference |
IV |
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ADAS |
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no |
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Call Number |
Admin @ si @ OSS2012b |
Serial |
2021 |
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Permanent link to this record |