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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
	Keywords
	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
	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
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ XFM2013			Serial	1822
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	Author	Ferran Diego; Joan Serrat; Antonio Lopez
	Title	Joint spatio-temporal alignment of sequences			Type	Journal Article
	Year	2013	Publication	IEEE Transactions on Multimedia	Abbreviated Journal	TMM
	Volume	15	Issue	6	Pages	1377-1387
	Keywords	video alignment
	Abstract	Video alignment is important in different areas of computer vision such as wide baseline matching, action recognition, change detection, video copy detection and frame dropping prevention. Current video alignment methods usually deal with a relatively simple case of fixed or rigidly attached cameras or simultaneous acquisition. Therefore, in this paper we propose a joint video alignment for bringing two video sequences into a spatio-temporal alignment. Specifically, the novelty of the paper is to formulate the video alignment to fold the spatial and temporal alignment into a single alignment framework. This simultaneously satisfies a frame-correspondence and frame-alignment similarity; exploiting the knowledge among neighbor frames by a standard pairwise Markov random field (MRF). This new formulation is able to handle the alignment of sequences recorded at different times by independent moving cameras that follows a similar trajectory, and also generalizes the particular cases that of fixed geometric transformation and/or linear temporal mapping. We conduct experiments on different scenarios such as sequences recorded simultaneously or by moving cameras to validate the robustness of the proposed approach. The proposed method provides the highest video alignment accuracy compared to the state-of-the-art methods on sequences recorded from vehicles driving along the same track at different times.
	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	1520-9210	ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ DSL2013; ADAS @ adas @			Serial	2228
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	Author	Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez
	Title	Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance			Type	Conference Article
	Year	2013	Publication	Proceedings of the International Conference on Computer Vision Theory and Applications	Abbreviated Journal
	Volume	1	Issue		Pages	153--161
	Keywords	Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model
	Abstract	Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability
	Address	Barcelona; February 2013
	Corporate Author				Thesis
	Publisher	SciTePress	Place of Publication	Portugal	Editor	Sebastiano Battiato and José Braz
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-989-8565-47-1	Medium
	Area	800	Expedition		Conference	VISAPP
	Notes	IAM;MV; 600.044; 600.047; 600.060; 605.203			Approved	no
	Call Number	IAM @ iam @ SGR2013			Serial	2123
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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.
	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	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	Lluis Pere de las Heras; David Fernandez; Ernest Valveny; Josep Llados; Gemma Sanchez
	Title	Unsupervised wall detector in architectural floor plan			Type	Conference Article
	Year	2013	Publication	12th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	1245-1249
	Keywords
	Abstract	Wall detection in floor plans is a crucial step in a complete floor plan recognition system. Walls define the main structure of buildings and convey essential information for the detection of other structural elements. Nevertheless, wall segmentation is a difficult task, mainly because of the lack of a standard graphical notation. The existing approaches are restricted to small group of similar notations or require the existence of pre-annotated corpus of input images to learn each new notation. In this paper we present an automatic wall segmentation system, with the ability to handle completely different notations without the need of any annotated dataset. It only takes advantage of the general knowledge that walls are a repetitive element, naturally distributed within the plan and commonly modeled by straight parallel lines. The method has been tested on four datasets of real floor plans with different notations, and compared with the state-of-the-art. The results show its suitability for different graphical notations, achieving higher recall rates than the rest of the methods while keeping a high average precision.
	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	ICDAR
	Notes	DAG; 600.061; 600.056; 600.045			Approved	no
	Call Number	Admin @ si @ HFV2013			Serial	2319
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	Author	Onur Ferhat; Fernando Vilariño
	Title	A Cheap Portable Eye-Tracker Solution for Common Setups			Type	Conference Article
	Year	2013	Publication	17th European Conference on Eye Movements	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Low cost; eye-tracker; software; webcam; Raspberry Pi
	Abstract	We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system. After assessing the accuracy of our eye-tracker in elaborated experiments involving 18 subjects under 4 different system setups, we developed a simple game to see how it performs in practice and we also installed it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.62° horizontal accuracy with 3 fps refresh rate for a building cost of 70 Euros.
	Address	Lund; Sweden; 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	ECEM
	Notes	MV;SIAI			Approved	no
	Call Number	Admin @ si @ FeV2013			Serial	2374
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	Author	Francesco Ciompi; Simone Balocco; Carles Caus; J. Mauri; Petia Radeva
	Title	Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images			Type	Conference Article
	Year	2013	Publication	16th International Conference on Medical Image Computing and Computer Assisted Intervention	Abbreviated Journal
	Volume	8150	Issue	2	Pages	345-352
	Keywords
	Abstract	We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm.
	Address	Nagoya; Japan; September 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	978-3-642-40762-8	Medium
	Area		Expedition		Conference	MICCAI
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ CBC2013			Serial	2258
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	Author	Joan Serrat; Felipe Lumbreras; Antonio Lopez
	Title	Cost estimation of custom hoses from STL files and CAD drawings			Type	Journal Article
	Year	2013	Publication	Computers in Industry	Abbreviated Journal	COMPUTIND
	Volume	64	Issue	3	Pages	299-309
	Keywords	On-line quotation; STL format; Regression; Gaussian process
	Abstract	We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	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
	Notes	ADAS; 600.057; 600.054; 605.203			Approved	no
	Call Number	Admin @ si @ SLL2013; ADAS @ adas @			Serial	2161
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	Author	Albert Gordo; Florent Perronnin; Ernest Valveny
	Title	Large-scale document image retrieval and classification with runlength histograms and binary embeddings			Type	Journal Article
	Year	2013	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	46	Issue	7	Pages	1898-1905
	Keywords	visual document descriptor; compression; large-scale; retrieval; classification
	Abstract	We present a new document image descriptor based on multi-scale runlength histograms. This descriptor does not rely on layout analysis and can be computed efficiently. We show how this descriptor can achieve state-of-theart results on two very different public datasets in classification and retrieval tasks. Moreover, we show how we can compress and binarize these descriptors to make them suitable for large-scale applications. We can achieve state-ofthe- art results in classification using binary descriptors of as few as 16 to 64 bits.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0031-3203	ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; 600.042; 600.045; 605.203			Approved	no
	Call Number	Admin @ si @ GPV2013			Serial	2306
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	Author	Fares Alnajar; Theo Gevers; Roberto Valenti; Sennay Ghebreab
	Title	Calibration-free Gaze Estimation using Human Gaze Patterns			Type	Conference Article
	Year	2013	Publication	15th IEEE International Conference on Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	137-144
	Keywords
	Abstract	We present a novel method to auto-calibrate gaze estimators based on gaze patterns obtained from other viewers. Our method is based on the observation that the gaze patterns of humans are indicative of where a new viewer will look at [12]. When a new viewer is looking at a stimulus, we first estimate a topology of gaze points (initial gaze points). Next, these points are transformed so that they match the gaze patterns of other humans to find the correct gaze points. In a flexible uncalibrated setup with a web camera and no chin rest, the proposed method was tested on ten subjects and ten images. The method estimates the gaze points after looking at a stimulus for a few seconds with an average accuracy of 4.3 im. Although the reported performance is lower than what could be achieved with dedicated hardware or calibrated setup, the proposed method still provides a sufficient accuracy to trace the viewer attention. This is promising considering the fact that auto-calibration is done in a flexible setup , without the use of a chin rest, and based only on a few seconds of gaze initialization data. To the best of our knowledge, this is the first work to use human gaze patterns in order to auto-calibrate gaze estimators.
	Address	Sydney
	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	ICCV
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ AGV2013			Serial	2365
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	Author	German Ros; J. Guerrero; Angel Sappa; Antonio Lopez
	Title	VSLAM pose initialization via Lie groups and Lie algebras optimization			Type	Conference Article
	Year	2013	Publication	Proceedings of IEEE International Conference on Robotics and Automation	Abbreviated Journal
	Volume		Issue		Pages	5740 - 5747
	Keywords	SLAM
	Abstract	We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm.
	Address	Karlsruhe; Germany; May 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	1050-4729	ISBN	978-1-4673-5641-1	Medium
	Area		Expedition		Conference	ICRA
	Notes	ADAS; 600.054; 600.055; 600.057			Approved	no
	Call Number	Admin @ si @ RGS2013a; ADAS @ adas @			Serial	2225
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	Author	Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers
	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	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	Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez
	Title	On-line lumen centre detection in gastrointestinal and respiratory endoscopy			Type	Conference Article
	Year	2013	Publication	Second International Workshop Clinical Image-Based Procedures	Abbreviated Journal
	Volume	8361	Issue		Pages	31-38
	Keywords	Lumen centre detection; Bronchoscopy; Colonoscopy
	Abstract	We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).
	Address	Nagoya; Japan; September 2013
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor	Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-319-05665-4	Medium
	Area	800	Expedition		Conference	CLIP
	Notes	MV; IAM; 600.047; 600.044; 600.060			Approved	no
	Call Number	Admin @ si @ SBG2013			Serial	2302
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	Author	Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez
	Title	Multi-task Bilinear Classifiers for Visual Domain Adaptation			Type	Conference Article
	Year	2013	Publication	Advances in Neural Information Processing Systems Workshop	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Domain Adaptation; Pedestrian Detection; ADAS
	Abstract	We propose a method that aims to lessen the significant accuracy degradation that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation. The bilinear classifier encodes the feature transformation and classification parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines.
	Address	Lake Tahoe; Nevada; USA; December 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	NIPSW
	Notes	ADAS; 600.054; 600.057; 601.217;ISE			Approved	no
	Call Number	ADAS @ adas @ XRH2013			Serial	2340
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	Author	Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet
	Title	Towards multispectral data acquisition with hand-held devices			Type	Conference Article
	Year	2013	Publication	20th IEEE International Conference on Image Processing	Abbreviated Journal
	Volume		Issue		Pages	2053 - 2057
	Keywords	Multispectral; mobile devices; color measurements
	Abstract	We propose a method to acquire multispectral data with handheld devices with front-mounted RGB cameras. We propose to use the display of the device as an illuminant while the camera captures images illuminated by the red, green and blue primaries of the display. Three illuminants and three response functions of the camera lead to nine response values which are used for reflectance estimation. Results are promising and show that the accuracy of the spectral reconstruction improves in the range from 30-40% over the spectral reconstruction based on a single illuminant. Furthermore, we propose to compute sensor-illuminant aware linear basis by discarding the part of the reflectances that falls in the sensorilluminant null-space. We show experimentally that optimizing reflectance estimation on these new basis functions decreases the RMSE significantly over basis functions that are independent to sensor-illuminant. We conclude that, multispectral data acquisition is potentially possible with consumer hand-held devices such as tablets, mobiles, and laptops, opening up applications which are currently considered to be unrealistic.
	Address	Melbourne; Australia; September 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	ICIP
	Notes	CIC; DAG; 600.048			Approved	no
	Call Number	Admin @ si @ KWK2013b			Serial	2265
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