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Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa |
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Title |
Evaluation of Similarity Functions in Multimodal Stereo |
Type |
Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
7324 |
Issue |
I |
Pages |
320-329 |
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Keywords |
Aveiro, Portugal |
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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. |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31294-6 |
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ICIAR |
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Notes |
ADAS |
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no |
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Call Number |
BLS2012a |
Serial |
2014 |
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Author |
Miguel Oliveira; Angel Sappa; V. Santos |
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Title |
Color Correction using 3D Gaussian Mixture Models |
Type |
Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
7324 |
Issue |
I |
Pages |
97-106 |
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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. |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
10.1007/978-3-642-31295-3_12 |
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ICIAR |
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ADAS |
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no |
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Call Number |
Admin @ si @ OSS2012a |
Serial |
2015 |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
6855 |
Issue |
II |
Pages |
463-470 |
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Keywords |
Pedestrian Detection; Color |
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Abstract |
Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution. |
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Address |
Seville, Spain |
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Publisher |
Springer |
Place of Publication |
Berlin Heidelberg |
Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
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Language |
English |
Summary Language |
english |
Original Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
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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 |
0302-9743 |
ISBN |
978-3-642-23677-8 |
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Conference |
CAIP |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ RVL2011b |
Serial |
1665 |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
Space Variant Representations for Mobile Platform Vision Applications |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
6855 |
Issue |
II |
Pages |
146-154 |
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Keywords |
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Abstract |
The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful in many vision applications. However, due to its nature, it fails in preserving features in the periphery. In the current work, as an attempt to overcome this problem, we propose a novel space-variant representation. It is evaluated and proved to be better than the log-polar representation in preserving the peripheral information, crucial for on-board mobile vision applications. The evaluation is performed by comparing log-polar and the proposed representation once they are used for estimating dense optical flow. |
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Address |
Seville, Spain |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
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Original Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-23677-8 |
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Expedition |
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Conference |
CAIP |
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Notes |
ADAS |
Approved |
no |
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Call Number |
NaS2011; ADAS @ adas @ |
Serial |
1686 |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Opponent Colors for Human Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
363-370 |
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Keywords |
Pedestrian Detection; Color; Part Based Models |
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Abstract |
Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer |
Place of Publication |
Berlin Heidelberg |
Editor |
J. Vitria; J.M. Sanches; M. Hernandez |
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Language |
English |
Summary Language |
English |
Original Title |
Opponent Colors for Human Detection |
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Series Title |
Lecture Notes on Computer Science |
Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ RVL2011a |
Serial |
1666 |
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Author |
Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados |
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Title |
Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval |
Type |
Conference Article |
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Year |
2011 |
Publication |
33rd European Conference on Information Retrieval |
Abbreviated Journal |
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Volume |
6611 |
Issue |
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Pages |
314-325 |
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Keywords |
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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. |
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Address |
Dublin, Ireland |
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Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch |
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LNCS |
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Series Volume |
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Edition |
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ISSN |
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ISBN |
978-3-642-20160-8 |
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Expedition |
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Conference |
ECIR |
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Notes |
DAG; RV;ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RAK2011 |
Serial |
1737 |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow |
Type |
Conference Article |
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Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
6111 |
Issue |
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Pages |
230-239 |
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Keywords |
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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. |
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Address |
Povoa de Varzim (Portugal) |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
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ICIAR |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ OnS2010 |
Serial |
1342 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
A Novel Approach to Geometric Fitting of Implicit Quadrics |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
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Volume |
5807 |
Issue |
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Pages |
121–132 |
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Abstract |
This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. |
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Address |
Bordeaux, France |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-04696-4 |
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Conference |
ACIVS |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ RoS2009 |
Serial |
1194 |
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Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
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Title |
Visual Registration Method For A Low Cost Robot: Computer Vision Systems |
Type |
Conference Article |
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Year |
2009 |
Publication |
7th International Conference on Computer Vision Systems |
Abbreviated Journal |
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Volume |
5815 |
Issue |
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Pages |
204–214 |
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Keywords |
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Abstract |
An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance. |
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Address |
Belgica |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
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Series Editor |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-04666-7 |
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Conference |
ICVS |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ ATR2009b |
Serial |
1247 |
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Author |
Juan A. Carvajal Ayala; Dennis Romero; Angel Sappa |
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Title |
Fine-tuning based deep convolutional networks for lepidopterous genus recognition |
Type |
Conference Article |
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Year |
2016 |
Publication |
21st Ibero American Congress on Pattern Recognition |
Abbreviated Journal |
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Issue |
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Pages |
467-475 |
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Abstract |
This paper describes an image classification approach oriented to identify specimens of lepidopterous insects at Ecuadorian ecological reserves. This work seeks to contribute to studies in the area of biology about genus of butterflies and also to facilitate the registration of unrecognized specimens. The proposed approach is based on the fine-tuning of three widely used pre-trained Convolutional Neural Networks (CNNs). This strategy is intended to overcome the reduced number of labeled images. Experimental results with a dataset labeled by expert biologists is presented, reaching a recognition accuracy above 92%. |
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Lima; Perú; November 2016 |
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LNCS |
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Conference |
CIARP |
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Notes |
ADAS; 600.086 |
Approved |
no |
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Call Number |
Admin @ si @ CRS2016 |
Serial |
2913 |
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