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Author | Marcelo D. Pistarelli; Angel Sappa; Ricardo Toledo | ||||
Title | Multispectral Stereo Image Correspondence | Type | Conference Article | ||
Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
Volume | 8048 | Issue | Pages | 217-224 | |
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Abstract | This paper presents a novel multispectral stereo image correspondence approach. It is evaluated using a stereo rig constructed with a visible spectrum camera and a long wave infrared spectrum camera. The novelty of the proposed approach lies on the usage of Hough space as a correspondence search domain. In this way it avoids searching for correspondence in the original multispectral image domains, where information is low correlated, and a common domain is used. The proposed approach is intended to be used in outdoor urban scenarios, where images contain large amount of edges. These edges are used as distinctive characteristics for the matching in the Hough space. Experimental results are provided showing the validity of the proposed approach. | ||||
Address | York; uk; August 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 | 978-3-642-40245-6 | Medium | |
Area | Expedition | Conference | CAIP | ||
Notes | ADAS; 600.055 | Approved | no | ||
Call Number | Admin @ si @ PST2013 | Serial | 2561 | ||
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Author | Gioacchino Vino; Angel Sappa | ||||
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 | |
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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 | ICIAR | ||
Notes | ADAS; 600.055 | Approved | no | ||
Call Number | Admin @ si @ ViS2013 | Serial | 2562 | ||
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Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
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 | ||||
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Area | Expedition | Conference | ICCVW-RR | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ XRV2013 | Serial | 2569 | ||
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Author | Marc Bolaños; Maite Garolera; Petia Radeva | ||||
Title | Active labeling application applied to food-related object recognition | Type | Conference Article | ||
Year | 2013 | Publication | 5th International Workshop on Multimedia for Cooking & Eating Activities | Abbreviated Journal | |
Volume | Issue | Pages | 45-50 | ||
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Abstract | Every day, lifelogging devices, available for recording different aspects of our daily life, increase in number, quality and functions, just like the multiple applications that we give to them. Applying wearable devices to analyse the nutritional habits of people is a challenging application based on acquiring and analyzing life records in long periods of time. However, to extract the information of interest related to the eating patterns of people, we need automatic methods to process large amount of life-logging data (e.g. recognition of food-related objects). Creating a rich set of manually labeled samples to train the algorithms is slow, tedious and subjective. To address this problem, we propose a novel method in the framework of Active Labeling for construct- ing a training set of thousands of images. Inspired by the hierarchical sampling method for active learning [6], we propose an Active forest that organizes hierarchically the data for easy and fast labeling. Moreover, introducing a classifier into the hierarchical structures, as well as transforming the feature space for better data clustering, additionally im- prove the algorithm. Our method is successfully tested to label 89.700 food-related objects and achieves significant reduction in expert time labelling.
Active labeling application applied to food-related object recognition ResearchGate. Available from: http://www.researchgate.net/publication/262252017Activelabelingapplicationappliedtofood-relatedobjectrecognition [accessed Jul 14, 2015]. |
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Address | Barcelona; October 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ACM-CEA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BGR2013b | Serial | 2637 | ||
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Author | Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados | ||||
Title | Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Address | Bethlehem; PA; USA; August 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | GREC | ||
Notes | DAG; 600.045; 600.061; 600.056 | Approved | no | ||
Call Number | Admin @ si @ HFF2013b | Serial | 2695 | ||
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Author | Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez | ||||
Title | Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
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Address | Bethlehem; PA; 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 | ISBN | Medium | |||
Area | Expedition | Conference | GREC | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ HVS2013b | Serial | 2696 | ||
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Author | Jose Manuel Alvarez; Theo Gevers; Antonio Lopez | ||||
Title | Evaluating Color Representation for Online Road Detection | Type | Conference Article | ||
Year | 2013 | Publication | ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars | Abbreviated Journal | |
Volume | Issue | Pages | 594-595 | ||
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Abstract | Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired using an on-board camera in different real-driving situations. |
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CVVT:E2M | ||
Notes | ADAS;ISE | Approved | no | ||
Call Number | Admin @ si @ AGL2013 | Serial | 2794 | ||
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Author | Kaida Xiao; Chenyang Fu; D.Mylonas; Dimosthenis Karatzas; S. Wuerger | ||||
Title | Unique Hue Data for Colour Appearance Models. Part ii: Chromatic Adaptation Transform | Type | Journal Article | ||
Year | 2013 | Publication | Color Research & Application | Abbreviated Journal | CRA |
Volume | 38 | Issue | 1 | Pages | 22-29 |
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Abstract | Unique hue settings of 185 observers under three room-lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013 | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ XFM2013 | Serial | 1822 | ||
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Author | David Vazquez | ||||
Title | Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection | Type | Book Whole | ||
Year | 2013 | Publication | PhD Thesis, Universitat de Barcelona-CVC | Abbreviated Journal | |
Volume | 1 | Issue | 1 | Pages | 1-105 |
Keywords | Pedestrian Detection; Domain Adaptation | ||||
Abstract | Pedestrian detection is of paramount interest for many applications, e.g. Advanced Driver Assistance Systems, Intelligent Video Surveillance and Multimedia systems. Most promising pedestrian detectors rely on appearance-based classifiers trained with annotated data. However, the required annotation step represents an intensive and subjective task for humans, what makes worth to minimize their intervention in this process by using computational tools like realistic virtual worlds. The reason to use these kind of tools relies in the fact that they allow the automatic generation of precise and rich annotations of visual information. Nevertheless, the use of this kind of data comes with the following question: can a pedestrian appearance model learnt with virtual-world data work successfully for pedestrian detection in real-world scenarios?. To answer this question, we conduct different experiments that suggest a positive answer. However, the pedestrian classifiers trained with virtual-world data can suffer the so called dataset shift problem as real-world based classifiers does. Accordingly, we have designed different domain adaptation techniques to face this problem, all of them integrated in a same framework (V-AYLA). We have explored different methods to train a domain adapted pedestrian classifiers by collecting a few pedestrian samples from the target domain (real world) and combining them with many samples of the source domain (virtual world). The extensive experiments we present show that pedestrian detectors developed within the V-AYLA framework do achieve domain adaptation. Ideally, we would like to adapt our system without any human intervention. Therefore, as a first proof of concept we also propose an unsupervised domain adaptation technique that avoids human intervention during the adaptation process. To the best of our knowledge, this Thesis work is the first demonstrating adaptation of virtual and real worlds for developing an object detector. Last but not least, we also assessed a different strategy to avoid the dataset shift that consists in collecting real-world samples and retrain with them in such a way that no bounding boxes of real-world pedestrians have to be provided. We show that the generated classifier is competitive with respect to the counterpart trained with samples collected by manually annotating pedestrian bounding boxes. The results presented on this Thesis not only end with a proposal for adapting a virtual-world pedestrian detector to the real world, but also it goes further by pointing out a new methodology that would allow the system to adapt to different situations, which we hope will provide the foundations for future research in this unexplored area. | ||||
Address | Barcelona | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Barcelona | Editor | Antonio Lopez;Daniel Ponsa |
Language | English | Summary Language | Original Title | ||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-84-940530-1-6 | Medium | ||
Area | Expedition | Conference | |||
Notes | adas | Approved | yes | ||
Call Number | ADAS @ adas @ Vaz2013 | Serial | 2276 | ||
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Author | Jose Manuel Alvarez; Theo Gevers; Ferran Diego; Antonio Lopez | ||||
Title | Road Geometry Classification by Adaptative Shape Models | Type | Journal Article | ||
Year | 2013 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
Volume | 14 | Issue | 1 | Pages | 459-468 |
Keywords | road detection | ||||
Abstract | Vision-based road detection is important for different applications in transportation, such as autonomous driving, vehicle collision warning, and pedestrian crossing detection. Common approaches to road detection are based on low-level road appearance (e.g., color or texture) and neglect of the scene geometry and context. Hence, using only low-level features makes these algorithms highly depend on structured roads, road homogeneity, and lighting conditions. Therefore, the aim of this paper is to classify road geometries for road detection through the analysis of scene composition and temporal coherence. Road geometry classification is proposed by building corresponding models from training images containing prototypical road geometries. We propose adaptive shape models where spatial pyramids are steered by the inherent spatial structure of road images. To reduce the influence of lighting variations, invariant features are used. Large-scale experiments show that the proposed road geometry classifier yields a high recognition rate of 73.57% ± 13.1, clearly outperforming other state-of-the-art methods. Including road shape information improves road detection results over existing appearance-based methods. Finally, it is shown that invariant features and temporal information provide robustness against disturbing imaging conditions. | ||||
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1524-9050 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS;ISE | Approved | no | ||
Call Number | Admin @ si @ AGD2013;; ADAS @ adas @ | Serial | 2269 | ||
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Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
Title | Multispectral Piecewise Planar Stereo using Manhattan-World Assumption | Type | Journal Article | ||
Year | 2013 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 34 | Issue | 1 | Pages | 52-61 |
Keywords | Multispectral stereo rig; Dense disparity maps from multispectral stereo; Color and infrared images | ||||
Abstract | This paper proposes a new framework for extracting dense disparity maps from a multispectral stereo rig. The system is constructed with an infrared and a color camera. It is intended to explore novel multispectral stereo matching approaches that will allow further extraction of semantic information. The proposed framework consists of three stages. Firstly, an initial sparse disparity map is generated by using a cost function based on feature matching in a multiresolution scheme. Then, by looking at the color image, a set of planar hypotheses is defined to describe the surfaces on the scene. Finally, the previous stages are combined by reformulating the disparity computation as a global minimization problem. The paper has two main contributions. The first contribution combines mutual information with a shape descriptor based on gradient in a multiresolution scheme. The second contribution, which is based on the Manhattan-world assumption, extracts a dense disparity representation using the graph cut algorithm. Experimental results in outdoor scenarios are provided showing the validity of the proposed framework. | ||||
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Notes | ADAS; 600.054; 600.055; 605.203 | Approved | no | ||
Call Number | Admin @ si @ BLS2013 | Serial | 2245 | ||
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Author | Laura Igual; Agata Lapedriza; Ricard Borras | ||||
Title | Robust Gait-Based Gender Classification using Depth Cameras | Type | Journal Article | ||
Year | 2013 | Publication | EURASIP Journal on Advances in Signal Processing | Abbreviated Journal | EURASIPJ |
Volume | 37 | Issue | 1 | Pages | 72-80 |
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Abstract | This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section. | ||||
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Notes | MILAB; OR;MV | Approved | no | ||
Call Number | Admin @ si @ ILB2013 | Serial | 2144 | ||
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Author | Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva | ||||
Title | Adaptable image cuts for motility inspection using WCE | Type | Journal Article | ||
Year | 2013 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
Volume | 37 | Issue | 1 | Pages | 72-80 |
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Abstract | The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE. | ||||
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Notes | MILAB; OR; 600.046; 605.203 | Approved | no | ||
Call Number | Admin @ si @ DSM2012 | Serial | 2151 | ||
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Author | Fadi Dornaika; Abdelmalik Moujahid; Bogdan Raducanu | ||||
Title | Facial expression recognition using tracked facial actions: Classifier performance analysis | Type | Journal Article | ||
Year | 2013 | Publication | Engineering Applications of Artificial Intelligence | Abbreviated Journal | EAAI |
Volume | 26 | Issue | 1 | Pages | 467-477 |
Keywords | Visual face tracking; 3D deformable models; Facial actions; Dynamic facial expression recognition; Human–computer interaction | ||||
Abstract | In this paper, we address the analysis and recognition of facial expressions in continuous videos. More precisely, we study classifiers performance that exploit head pose independent temporal facial action parameters. These are provided by an appearance-based 3D face tracker that simultaneously provides the 3D head pose and facial actions. The use of such tracker makes the recognition pose- and texture-independent. Two different schemes are studied. The first scheme adopts a dynamic time warping technique for recognizing expressions where training data are given by temporal signatures associated with different universal facial expressions. The second scheme models temporal signatures associated with facial actions with fixed length feature vectors (observations), and uses some machine learning algorithms in order to recognize the displayed expression. Experiments quantified the performance of different schemes. These were carried out on CMU video sequences and home-made video sequences. The results show that the use of dimension reduction techniques on the extracted time series can improve the classification performance. Moreover, these experiments show that the best recognition rate can be above 90%. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
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Notes | OR; 600.046;MV | Approved | no | ||
Call Number | Admin @ si @ DMR2013 | Serial | 2185 | ||
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Author | Naveen Onkarappa; Angel Sappa | ||||
Title | A Novel Space Variant Image Representation | Type | Journal Article | ||
Year | 2013 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
Volume | 47 | Issue | 1-2 | Pages | 48-59 |
Keywords | Space-variant representation; Log-polar mapping; Onboard vision applications | ||||
Abstract | Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 0924-9907 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS; 600.055; 605.203; 601.215 | Approved | no | ||
Call Number | Admin @ si @ OnS2013a | Serial | 2243 | ||
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