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Author |
Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny |
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Title |
Efficient Exemplar Word Spotting |
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Conference Article |
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Year |
2012 |
Publication |
23rd British Machine Vision Conference |
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67.1- 67.11 |
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Abstract |
In this paper we propose an unsupervised segmentation-free method for word spotting in document images.
Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage. |
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1-901725-46-4 |
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BMVC |
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DAG |
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no |
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DAG @ dag @ AGF2012 |
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1984 |
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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 |
Type |
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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ISSN |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
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ICPR |
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ADAS |
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no |
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Call Number |
Admin @ si @ RSL2012a; |
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2032 |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
A medial map capturing the essential geometry of organs |
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Conference Article |
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Year |
2012 |
Publication |
ISBI Workshop on Open Source Medical Image Analysis software |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
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1691 - 1694 |
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Keywords |
Medial Surface Representation, Volume Reconstruction,Geometry , Image reconstruction , Liver , Manifolds , Shape , Surface morphology , Surface reconstruction |
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Abstract |
Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Accurate computation of one pixel wide medial surfaces is mandatory. Those surfaces must represent faithfully the geometry of the volume. Although morphological methods produce excellent results in 2D, their complexity and quality drops across dimensions, due to a more complex description of pixel neighborhoods. This paper introduces a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Our experiments show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume |
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Barcelona,Spain |
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IEEE |
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ISSN |
1945-7928 |
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978-1-4577-1857-1 |
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ISBI |
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IAM |
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no |
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Call Number |
IAM @ iam @ VGG2012a |
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1989 |
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Author |
Wenjuan Gong; Jordi Gonzalez; Xavier Roca |
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Title |
Human Action Recognition based on Estimated Weak Poses |
Type |
Journal Article |
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Year |
2012 |
Publication |
EURASIP Journal on Advances in Signal Processing |
Abbreviated Journal |
EURASIPJ |
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Abstract |
We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method. |
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Notes |
ISE |
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no |
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Call Number |
Admin @ si @ GGR2012 |
Serial |
2003 |
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Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Monocular Egomotion Estimation based on Image Matching |
Type |
Conference Article |
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Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
Abbreviated Journal |
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Pages |
425-430 |
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Keywords |
SLAM |
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Address |
Portugal |
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ICPRAM |
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ADAS |
Approved |
no |
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Call Number |
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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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
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Pages |
323-328 |
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Abstract |
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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Conference |
VISAPP |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e |
Serial |
2012 |
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Permanent link to this record |
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Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Pedestrian Candidates Generation using Monocular Cues |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
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Pages |
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 |
Approved |
no |
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Call Number |
Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d |
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2013 |
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Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Planar-Based Multispectral Stereo |
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 |
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 |
![download PDF file pdf](img/file_PDF.gif)
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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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Author |
Monica Piñol; Angel Sappa; Angeles Lopez; Ricardo Toledo |
![download PDF file pdf](img/file_PDF.gif)
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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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Author |
German Ros; Angel Sappa; Daniel Ponsa; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
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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 |
Approved |
no |
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Call Number |
Admin @ si @ RSP2012; ADAS @ adas |
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2019 |
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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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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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1931-0587 |
ISBN |
978-1-4673-2119-8 |
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IV |
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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 |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
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299-303 |
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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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IEEE Xplore |
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1931-0587 |
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978-1-4673-2119-8 |
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IV |
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ADAS |
Approved |
no |
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Call Number |
Admin @ si @ OSS2012b |
Serial |
2021 |
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Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
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Title |
AVA: A Large-Scale Database for Aesthetic Visual Analysis |
Type |
Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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2408-2415 |
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Abstract |
With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks |
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Providence, Rhode Islan |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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Admin @ si @ MMP2012a |
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2025 |
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Author |
Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell |
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Title |
Names and Shades of Color for Intrinsic Image Estimation |
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Conference Article |
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Year |
2012 |
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25th IEEE Conference on Computer Vision and Pattern Recognition |
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278-285 |
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Abstract |
In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance. |
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Providence, Rhode Island |
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Publisher |
IEEE Xplore |
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Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
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Conference |
CVPR |
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CIC |
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no |
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Call Number |
Admin @ si @ SPB2012 |
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2026 |
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Permanent link to this record |