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Author Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez edit  openurl
  Title DA-DPM Pedestrian Detection Type Conference Article
  Year 2013 Publication ICCV Workshop on Reconstruction meets Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords Domain Adaptation; Pedestrian Detection  
  Abstract  
  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 (up) ICCVW-RR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ XRV2013 Serial 2569  
Permanent link to this record
 

 
Author Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers edit   pdf
openurl 
  Title Adapting Pedestrian Detection from Synthetic to Far Infrared Images Type Conference Article
  Year 2013 Publication ICCV Workshop on Visual Domain Adaptation and Dataset Bias Abbreviated Journal  
  Volume Issue Pages  
  Keywords Domain Adaptation; Far Infrared; Pedestrian Detection  
  Abstract We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes.  
  Address Sydney; Australia; December 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Sydney, Australy Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (up) ICCVW-VisDA  
  Notes ADAS; 600.054; 600.055; 600.057; 601.217;ISE Approved no  
  Call Number ADAS @ adas @ SRV2013 Serial 2334  
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Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados edit  url
doi  openurl
  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 (up) ICDAR  
  Notes DAG;ADAS Approved no  
  Call Number Admin @ si @ RAT2011 Serial 1788  
Permanent link to this record
 

 
Author David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados edit   pdf
doi  openurl
  Title Integrating Visual and Textual Cues for Query-by-String Word Spotting Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 511 - 515  
  Keywords  
  Abstract In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances.  
  Address Washington; USA; August 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 1520-5363 ISBN Medium  
  Area Expedition Conference (up) ICDAR  
  Notes DAG; ADAS; 600.045; 600.055; 600.061 Approved no  
  Call Number Admin @ si @ ART2013 Serial 2224  
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Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados edit   pdf
doi  openurl
  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 (up) 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 Patricia Suarez; Angel Sappa; Boris X. Vintimilla edit   pdf
openurl 
  Title Colorizing Infrared Images through a Triplet Conditional DCGAN Architecture Type Conference Article
  Year 2017 Publication 19th international conference on image analysis and processing Abbreviated Journal  
  Volume Issue Pages  
  Keywords CNN in Multispectral Imaging; Image Colorization  
  Abstract This paper focuses on near infrared (NIR) image colorization by using a Conditional Deep Convolutional Generative Adversarial Network (CDCGAN) architecture model. The proposed architecture is based on the usage of a conditional probabilistic generative model. Firstly, it learns to colorize the given input image, by using a triplet model architecture that tackle every channel in an independent way. In the proposed model, the nal layer of red channel consider the infrared image to enhance the details, resulting in a sharp RGB image. Then, in the second stage, a discriminative model is used to estimate the probability that the generated image came from the training dataset, rather than the image automatically generated. Experimental results with a large set of real images are provided showing the validity of the proposed approach. Additionally, the proposed approach is compared with a state of the art approach showing better results.  
  Address Catania; Italy; September 2017  
  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 (up) ICIAP  
  Notes ADAS; MSIAU; 600.086; 600.122; 600.118 Approved no  
  Call Number Admin @ si @ SSV2017c Serial 3016  
Permanent link to this record
 

 
Author Naveen Onkarappa; Angel Sappa edit  doi
isbn  openurl
  Title On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow Type Conference Article
  Year 2010 Publication 7th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 6111 Issue Pages 230-239  
  Keywords  
  Abstract This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach.  
  Address Povoa de Varzim (Portugal)  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-13771-6 Medium  
  Area Expedition Conference (up) ICIAR  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ OnS2010 Serial 1342  
Permanent link to this record
 

 
Author Fernando Barrera; Felipe Lumbreras; Angel Sappa edit   pdf
doi  isbn
openurl 
  Title Evaluation of Similarity Functions in Multimodal Stereo Type Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7324 Issue I Pages 320-329  
  Keywords Aveiro, Portugal  
  Abstract This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31294-6 Medium  
  Area Expedition Conference (up) ICIAR  
  Notes ADAS Approved no  
  Call Number BLS2012a Serial 2014  
Permanent link to this record
 

 
Author Miguel Oliveira; Angel Sappa; V. Santos edit   pdf
doi  isbn
openurl 
  Title Color Correction using 3D Gaussian Mixture Models Type Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7324 Issue I Pages 97-106  
  Keywords  
  Abstract The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight 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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 10.1007/978-3-642-31295-3_12 Medium  
  Area Expedition Conference (up) ICIAR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ OSS2012a Serial 2015  
Permanent link to this record
 

 
Author Gioacchino Vino; Angel Sappa edit  doi
isbn  openurl
  Title Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach Type Conference Article
  Year 2013 Publication 10th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7950 Issue Pages 354-363  
  Keywords  
  Abstract This paper presents an adaptive thresholding approach intended to increase the number of detected corners, while reducing the amount of those ones corresponding to noisy data. The proposed approach works by using the classical Harris corner detector algorithm and overcome the difficulty in finding a general threshold that work well for all the images in a given data set by proposing a novel adaptive thresholding scheme. Initially, two thresholds are used to discern between strong corners and flat regions. Then, a region based criteria is used to discriminate between weak corners and noisy points in the midway interval. Experimental results show that the proposed approach has a better capability to reject false corners and, at the same time, to detect weak ones. Comparisons with the state of the art are provided showing the validity of the proposed approach.  
  Address Póvoa de Varzim; Portugal; June 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-39093-7 Medium  
  Area Expedition Conference (up) ICIAR  
  Notes ADAS; 600.055 Approved no  
  Call Number Admin @ si @ ViS2013 Serial 2562  
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