| |
Records |
Links |
|
Author |
Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers |
|
| |
Title |
Improving HOG with Image Segmentation: Application to Human Detection |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
11th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
|
|
| |
Volume |
7517 |
Issue |
|
Pages |
178-189 |
|
| |
Keywords |
Segmentation; Pedestrian Detection |
|
| |
Abstract  |
In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function. |
|
| |
Address |
Brno, Czech Republic |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
J. Blanc-Talon et al. |
|
| |
Language |
English |
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-33139-8 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ACIVS |
|
| |
Notes |
ADAS;ISE |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SLV2012 |
Serial |
1980 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
|
| |
Title |
Efficient Object Pixel-Level Categorization using Bag of Features: Advances in Visual Computing |
Type |
Conference Article |
| |
Year |
2009 |
Publication |
5th International Symposium on Visual Computing |
Abbreviated Journal |
|
|
| |
Volume |
5875 |
Issue |
|
Pages |
44–55 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we present a pixel-level object categorization method suitable to be applied under real-time constraints. Since pixels are categorized using a bag of features scheme, the major bottleneck of such an approach would be the feature pooling in local histograms of visual words. Therefore, we propose to bypass this time-consuming step and directly obtain the score from a linear Support Vector Machine classifier. This is achieved by creating an integral image of the components of the SVM which can readily obtain the classification score for any image sub-window with only 10 additions and 2 products, regardless of its size. Besides, we evaluated the performance of two efficient feature quantization methods: the Hierarchical K-Means and the Extremely Randomized Forest. All experiments have been done in the Graz02 database, showing comparable, or even better results to related work with a lower computational cost. |
|
| |
Address |
Las Vegas, USA |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-642-10330-8 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ISVC |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ ATR2009a |
Serial |
1246 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Ariel Amato; Angel Sappa; Alicia Fornes; Felipe Lumbreras; Josep Llados |
|
| |
Title |
Divide and Conquer: Atomizing and Parallelizing A Task in A Mobile Crowdsourcing Platform |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
2nd International ACM Workshop on Crowdsourcing for Multimedia |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
21-22 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we present some conclusions about the advantages of having an efficient task formulation when a crowdsourcing platform is used. In particular we show how the task atomization and distribution can help to obtain results in an efficient way. Our proposal is based on a recursive splitting of the original task into a set of smaller and simpler tasks. As a result both more accurate and faster solutions are obtained. Our evaluation is performed on a set of ancient documents that need to be digitized. |
|
| |
Address |
Barcelona; October 2013 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-1-4503-2396-3 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CrowdMM |
|
| |
Notes |
ADAS; ISE; DAG; 600.054; 600.055; 600.045; 600.061; 602.006 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ SLA2013 |
Serial |
2335 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Cristina Cañero; Petia Radeva; Oriol Pujol; Ricardo Toledo; Debora Gil; J. Saludes; Juan J. Villanueva; B. Garcia del Blanco; Josefina Mauri; Eduard Fernandez-Nofrerias; J.A. Gomez-Hospital; E. Iraculis; J. Comin; C. Quiles; F. Jara; A. Cequier; E.Esplugas |
|
| |
Title |
Three-dimensional reconstruction and quantification of the coronary tree using intravascular ultrasound images |
Type |
Conference Article |
| |
Year |
1999 |
Publication |
Proceedings of International Conference on Computer in Cardiology (CIC´99) |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we propose a new Computer Vision technique to reconstruct the vascular wall in space using a deformable model-based technique and compounding methods, based in biplane angiography and intravascular ultrasound data jicsion. It is also proposed a generalpurpose three-dimensional guided interpolation method. The three dimensional centerline of the vessel is reconstructed from geometrically corrected biplane angiographies using automatic segmentation methods and snakes. The IVUS image planes are located in the threedimensional space and correctly oriented. A led interpolation method based in B-SurJaces and snakes isused to fill the gaps among image planes |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CINC99 |
|
| |
Notes |
MILAB;RV;IAM;ADAS;HuPBA |
Approved |
no |
|
| |
Call Number |
IAM @ iam @ CRP1999b |
Serial |
1492 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Xialei Liu; Marc Masana; Luis Herranz; Joost Van de Weijer; Antonio Lopez; Andrew Bagdanov |
|
| |
Title |
Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting |
Type |
Conference Article |
| |
Year |
2018 |
Publication |
24th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
2262-2268 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we propose an approach to avoiding catastrophic forgetting in sequential task learning scenarios. Our technique is based on a network reparameterization that approximately diagonalizes the Fisher Information Matrix of the network parameters. This reparameterization takes the form of
a factorized rotation of parameter space which, when used in conjunction with Elastic Weight Consolidation (which assumes a diagonal Fisher Information Matrix), leads to significantly better performance on lifelong learning of sequential tasks. Experimental results on the MNIST, CIFAR-100, CUB-200 and
Stanford-40 datasets demonstrate that we significantly improve the results of standard elastic weight consolidation, and that we obtain competitive results when compared to the state-of-the-art in lifelong learning without forgetting. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
LAMP; ADAS; 601.305; 601.109; 600.124; 600.106; 602.200; 600.120; 600.118 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ LMH2018 |
Serial |
3160 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados |
|
| |
Title |
Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval |
Type |
Conference Article |
| |
Year |
2011 |
Publication |
33rd European Conference on Information Retrieval |
Abbreviated Journal |
|
|
| |
Volume |
6611 |
Issue |
|
Pages |
314-325 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset. |
|
| |
Address |
Dublin, Ireland |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-642-20160-8 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ECIR |
|
| |
Notes |
DAG; RV;ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RAK2011 |
Serial |
1737 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
|
| |
Title |
Monocular Depth-based Background Estimation |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
7th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
323-328 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
Roma |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
VISAPP |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e |
Serial |
2012 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
|
| |
Title |
Towards Query-by-Speech Handwritten Keyword Spotting |
Type |
Conference Article |
| |
Year |
2015 |
Publication |
13th International Conference on Document Analysis and Recognition ICDAR2015 |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
501-505 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper, we present a new querying paradigm for handwritten keyword spotting. We propose to represent handwritten word images both by visual and audio representations, enabling a query-by-speech keyword spotting system. The two representations are merged together and projected to a common sub-space in the training phase. This transform allows to, given a spoken query, retrieve word instances that were only represented by the visual modality. In addition, the same method can be used backwards at no additional cost to produce a handwritten text-tospeech system. We present our first results on this new querying mechanism using synthetic voices over the George Washington
dataset. |
|
| |
Address |
Nancy; France; August 2015 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG; 600.084; 600.061; 601.223; 600.077;ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RAT2015b |
Serial |
2682 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias |
|
| |
Title |
Scene Representations for Autonomous Driving: an approach based on polygonal primitives |
Type |
Conference Article |
| |
Year |
2015 |
Publication |
2nd Iberian Robotics Conference ROBOT2015 |
Abbreviated Journal |
|
|
| |
Volume |
417 |
Issue |
|
Pages |
503-515 |
|
| |
Keywords |
Scene reconstruction; Point cloud; Autonomous vehicles |
|
| |
Abstract |
In this paper, we present a novel methodology to compute a 3D scene
representation. The algorithm uses macro scale polygonal primitives to model the scene. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Results show that the approach is capable of producing accurate descriptions of the scene. In addition, the algorithm is very efficient when compared to other techniques. |
|
| |
Address |
Lisboa; Portugal; November 2015 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ROBOT |
|
| |
Notes |
ADAS; 600.076; 600.086 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ OSS2015a |
Serial |
2662 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
|
| |
Title |
Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method |
Type |
Conference Article |
| |
Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
63-67 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts. |
|
| |
Address |
Beijing, China |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG;ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RAT2011 |
Serial |
1788 |
|
| Permanent link to this record |
