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	Author	C. Alejandro Parraga; Javier Vazquez; Maria Vanrell
	Title	A new cone activation-based natural images dataset			Type	Journal Article
	Year	2009	Publication	Perception	Abbreviated Journal	PER
	Volume	36	Issue		Pages	180
	Keywords
	Abstract	We generated a new dataset of digital natural images where each colour plane corresponds to the human LMS (long-, medium-, short-wavelength) cone activations. The images were chosen to represent five different visual environments (eg forest, seaside, mountain snow, urban, motorways) and were taken under natural illumination at different times of day. At the bottom-left corner of each picture there was a matte grey ball of approximately constant spectral reflectance (across the camera's response spectrum,) and nearly Lambertian reflective properties, which allows to compute (and remove, if necessary) the illuminant's colour and intensity. The camera (Sigma Foveon SD10) was calibrated by measuring its sensor's spectral responses using a set of 31 spectrally narrowband interference filters. This allowed conversion of the final camera-dependent RGB colour space into the Smith and Pokorny (1975) cone activation space by means of a polynomial transformation, optimised for a set of 1269 Munsell chip reflectances. This new method is an improvement over the usual 3 × 3 matrix transformation which is only accurate for spectrally-narrowband colours. The camera-to-LMS transformation can be recalculated to consider other non-human visual systems. The dataset is available to download from our website.
	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	CIC			Approved	no
	Call Number	CAT @ cat @ PVV2009			Serial	1193
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	Author	C. Alejandro Parraga; Jordi Roca; Dimosthenis Karatzas; Sophie Wuerger
	Title	Limitations of visual gamma corrections in LCD displays			Type	Journal Article
	Year	2014	Publication	Displays	Abbreviated Journal	Dis
	Volume	35	Issue	5	Pages	227–239
	Keywords	Display calibration; Psychophysics; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration
	Abstract	A method for estimating the non-linear gamma transfer function of liquid–crystal displays (LCDs) without the need of a photometric measurement device was described by Xiao et al. (2011) [1]. It relies on observer’s judgments of visual luminance by presenting eight half-tone patterns with luminances from 1/9 to 8/9 of the maximum value of each colour channel. These half-tone patterns were distributed over the screen both over the vertical and horizontal viewing axes. We conducted a series of photometric and psychophysical measurements (consisting in the simultaneous presentation of half-tone patterns in each trial) to evaluate whether the angular dependency of the light generated by three different LCD technologies would bias the results of these gamma transfer function estimations. Our results show that there are significant differences between the gamma transfer functions measured and produced by observers at different viewing angles. We suggest appropriate modifications to the Xiao et al. paradigm to counterbalance these artefacts which also have the advantage of shortening the amount of time spent in collecting the psychophysical measurements.
	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	CIC; DAG; 600.052; 600.077; 600.074			Approved	no
	Call Number	Admin @ si @ PRK2014			Serial	2511
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	Author	C. Alejandro Parraga; Jordi Roca; Maria Vanrell
	Title	Do Basic Colors Influence Chromatic Adaptation?			Type	Journal Article
	Year	2011	Publication	Journal of Vision	Abbreviated Journal	VSS
	Volume	11	Issue	11	Pages	85
	Keywords
	Abstract	Color constancy (the ability to perceive colors relatively stable under different illuminants) is the result of several mechanisms spread across different neural levels and responding to several visual scene cues. It is usually measured by estimating the perceived color of a grey patch under an illuminant change. In this work, we hypothesize whether chromatic adaptation (without a reference white or grey) could be driven by certain colors, specifically those corresponding to the universal color terms proposed by Berlin and Kay (1969). To this end we have developed a new psychophysical paradigm in which subjects adjust the color of a test patch (in CIELab space) to match their memory of the best example of a given color chosen from the universal terms list (grey, red, green, blue, yellow, purple, pink, orange and brown). The test patch is embedded inside a Mondrian image and presented on a calibrated CRT screen inside a dark cabin. All subjects were trained to “recall” their most exemplary colors reliably from memory and asked to always produce the same basic colors when required under several adaptation conditions. These include achromatic and colored Mondrian backgrounds, under a simulated D65 illuminant and several colored illuminants. A set of basic colors were measured for each subject under neutral conditions (achromatic background and D65 illuminant) and used as “reference” for the rest of the experiment. The colors adjusted by the subjects in each adaptation condition were compared to the reference colors under the corresponding illuminant and a “constancy index” was obtained for each of them. Our results show that for some colors the constancy index was better than for grey. The set of best adapted colors in each condition were common to a majority of subjects and were dependent on the chromaticity of the illuminant and the chromatic background considered.
	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	1534-7362	ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ PRV2011			Serial	1759
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	Author	C. Alejandro Parraga; Olivier Penacchio; Maria Vanrell
	Title	Retinal Filtering Matches Natural Image Statistics at Low Luminance Levels			Type	Journal Article
	Year	2011	Publication	Perception	Abbreviated Journal	PER
	Volume	40	Issue		Pages	96
	Keywords
	Abstract	The assumption that the retina’s main objective is to provide a minimum entropy representation to higher visual areas (ie efficient coding principle) allows to predict retinal filtering in space–time and colour (Atick, 1992 Network 3 213–251). This is achieved by considering the power spectra of natural images (which is proportional to 1/f2) and the suppression of retinal and image noise. However, most studies consider images within a limited range of lighting conditions (eg near noon) whereas the visual system’s spatial filtering depends on light intensity and the spatiochromatic properties of natural scenes depend of the time of the day. Here, we explore whether the dependence of visual spatial filtering on luminance match the changes in power spectrum of natural scenes at different times of the day. Using human cone-activation based naturalistic stimuli (from the Barcelona Calibrated Images Database), we show that for a range of luminance levels, the shape of the retinal CSF reflects the slope of the power spectrum at low spatial frequencies. Accordingly, the retina implements the filtering which best decorrelates the input signal at every luminance level. This result is in line with the body of work that places efficient coding as a guiding neural principle.
	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	CIC			Approved	no
	Call Number	Admin @ si @ PPV2011			Serial	1720
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	Author	C. Alejandro Parraga; Robert Benavente; Maria Vanrell
	Title	Towards a general model of colour categorization which considers context			Type	Journal Article
	Year	2010	Publication	Perception. ECVP Abstract Supplement	Abbreviated Journal	PER
	Volume	39	Issue		Pages	86
	Keywords
	Abstract	In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured. In the ﬁrst experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to ﬁnd the boundary between pairs of adjacent colours. Results from these experiments showed signiﬁcant dierences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the dierences in the paradigms used. In this work, we settle this question by repeating the ﬁrst experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that although boundary locations are very similar, boundaries measured in context are signiﬁcantly dierent(more diuse) than those measured in isolation (conﬁrmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space.
	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	CIC			Approved	no
	Call Number	CAT @ cat @ PBV2010b			Serial	1326
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	Author	C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich
	Title	Psychophysical measurements to model inter-colour regions of colour-naming space			Type	Journal Article
	Year	2009	Publication	Journal of Imaging Science and Technology	Abbreviated Journal
	Volume	53	Issue	3	Pages	031106 (8 pages)
	Keywords	image processing; Analysis
	Abstract	JCR Impact Factor 2009: 0.391 In this paper, we present a fuzzy-set of parametric functions which segment the CIE lab space into eleven regions which correspond to the group of common universal categories present in all evolved languages as identified by anthropologists and linguists. The set of functions is intended to model a color-name assignment task by humans and differs from other models in its emphasis on the inter-color boundary regions, which were explicitly measured by means of a psychophysics experiment. In our particular implementation, the CIE lab space was segmented into eleven color categories using a Triple Sigmoid as the fuzzy sets basis, whose parameters are included in this paper. The modelâ€™s parameters were adjusted according to the psychophysical results of a yes/no discrimination paradigm where observers had to choose (English) names for isoluminant colors belonging to regions in-between neighboring categories. These colors were presented on a calibrated CRT monitor (14-bit x 3 precision). The experimental results show that inter- color boundary regions are much less defined than expected and color samples other than those near the most representatives are needed to define the position and shape of boundaries between categories. The extended set of model parameters is given as a table.
	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	CIC			Approved	no
	Call Number	CAT @ cat @ PBV2009			Serial	1157
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	Author	C. Butakoff; Simone Balocco; F.M. Sukno; C. Hoogendoorn; C. Tobon-Gomez; G. Avegliano; A.F. Frangi
	Title	Left-ventricular Epi- and Endocardium Extraction from 3D Ultrasound Images Using an Automatically Constructed 3D ASM			Type	Journal Article
	Year	2016	Publication	Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization	Abbreviated Journal	CMBBE
	Volume	4	Issue	5	Pages	265-280
	Keywords	ASM; cardiac segmentation; statistical model; shape model; 3D ultrasound; cardiac segmentation
	Abstract	In this paper, we propose an automatic method for constructing an active shape model (ASM) to segment the complete cardiac left ventricle in 3D ultrasound (3DUS) images, which avoids costly manual landmarking. The automatic construction of the ASM has already been addressed in the literature; however, the direct application of these methods to 3DUS is hampered by a high level of noise and artefacts. Therefore, we propose to construct the ASM by fusing the multidetector computed tomography data, to learn the shape, with the artificially generated 3DUS, in order to learn the neighbourhood of the boundaries. Our artificial images were generated by two approaches: a faster one that does not take into account the geometry of the transducer, and a more comprehensive one, implemented in Field II toolbox. The segmentation accuracy of our ASM was evaluated on 20 patients with left-ventricular asynchrony, demonstrating plausibility of the approach.
	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	2168-1163	ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ BBS2016			Serial	2449
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	Author	Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez
	Title	Determining the Best Suited Semantic Events for Cognitive Surveillance			Type	Journal Article
	Year	2011	Publication	Expert Systems with Applications	Abbreviated Journal	EXSY
	Volume	38	Issue	4	Pages	4068–4079
	Keywords	Cognitive surveillance; Event modeling; Content-based video retrieval; Ontologies; Advanced user interfaces
	Abstract	State-of-the-art systems on cognitive surveillance identify and describe complex events in selected domains, thus providing end-users with tools to easily access the contents of massive video footage. Nevertheless, as the complexity of events increases in semantics and the types of indoor/outdoor scenarios diversify, it becomes difficult to assess which events describe better the scene, and how to model them at a pixel level to fulfill natural language requests. We present an ontology-based methodology that guides the identification, step-by-step modeling, and generalization of the most relevant events to a specific domain. Our approach considers three steps: (1) end-users provide textual evidence from surveilled video sequences; (2) transcriptions are analyzed top-down to build the knowledge bases for event description; and (3) the obtained models are used to generalize event detection to different image sequences from the surveillance domain. This framework produces user-oriented knowledge that improves on existing advanced interfaces for video indexing and retrieval, by determining the best suited events for video understanding according to end-users. We have conducted experiments with outdoor and indoor scenes showing thefts, chases, and vandalism, demonstrating the feasibility and generalization of this proposal.
	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	ISE			Approved	no
	Call Number	Admin @ si @ FBR2011a			Serial	1722
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	Author	Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez
	Title	Augmenting Video Surveillance Footage with Virtual Agents for Incremental Event Evaluation			Type	Journal Article
	Year	2011	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	32	Issue	6	Pages	878–889
	Keywords
	Abstract	The fields of segmentation, tracking and behavior analysis demand for challenging video resources to test, in a scalable manner, complex scenarios like crowded environments or scenes with high semantics. Nevertheless, existing public databases cannot scale the presence of appearing agents, which would be useful to study long-term occlusions and crowds. Moreover, creating these resources is expensive and often too particularized to specific needs. We propose an augmented reality framework to increase the complexity of image sequences in terms of occlusions and crowds, in a scalable and controllable manner. Existing datasets can be increased with augmented sequences containing virtual agents. Such sequences are automatically annotated, thus facilitating evaluation in terms of segmentation, tracking, and behavior recognition. In order to easily specify the desired contents, we propose a natural language interface to convert input sentences into virtual agent behaviors. Experimental tests and validation in indoor, street, and soccer environments are provided to show the feasibility of the proposed approach in terms of robustness, scalability, and semantics.
	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	ISE			Approved	no
	Call Number	Admin @ si @ FBR2011b			Serial	1723
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	Author	Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Antoni Rosell; Marta Diez-Ferrer; Debora Gil
	Title	Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy			Type	Journal Article
	Year	2015	Publication	International Journal of Computer Assisted Radiology and Surgery	Abbreviated Journal	IJCAR
	Volume	10	Issue	6	Pages	935-945
	Keywords
	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
	Notes	IAM; MV; 600.075			Approved	no
	Call Number	Admin @ si @ SBS2015a			Serial	2611
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	Author	Carlo Gatta; Eloi Puertas; Oriol Pujol
	Title	Multi-Scale Stacked Sequential Learning			Type	Journal Article
	Year	2011	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	44	Issue	10-11	Pages	2414-2416
	Keywords	Stacked sequential learning; Multiscale; Multiresolution; Contextual classification
	Abstract	One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ GPP2011			Serial	1802
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	Author	Carlo Gatta; Francesco Ciompi
	Title	Stacked Sequential Scale-Space Taylor Context			Type	Journal Article
	Year	2014	Publication	IEEE Transactions on Pattern Analysis and Machine Intelligence	Abbreviated Journal	TPAMI
	Volume	36	Issue	8	Pages	1694-1700
	Keywords
	Abstract	We analyze sequential image labeling methods that sample the posterior label field in order to gather contextual information. We propose an effective method that extracts local Taylor coefficients from the posterior at different scales. Results show that our proposal outperforms state-of-the-art methods on MSRC-21, CAMVID, eTRIMS8 and KAIST2 data sets.
	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	0162-8828	ISBN		Medium
	Area		Expedition		Conference
	Notes	LAMP; MILAB; 601.160; 600.079			Approved	no
	Call Number	Admin @ si @ GaC2014			Serial	2466
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	Author	Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. M. Ferre; Petia Radeva
	Title	Fast Rigid Registration of Vascular Structures in IVUS Sequences			Type	Journal Article
	Year	2009	Publication	IEEE Transactions on Information Technology in Biomedicine	Abbreviated Journal
	Volume	13	Issue	6	Pages	106-1011
	Keywords
	Abstract	Intravascular ultrasound (IVUS) technology permits visualization of high-resolution images of internal vascular structures. IVUS is a unique image-guiding tool to display longitudinal view of the vessels, and estimate the length and size of vascular structures with the goal of accurate diagnosis. Unfortunately, due to pulsatile contraction and expansion of the heart, the captured images are affected by different motion artifacts that make visual inspection difficult. In this paper, we propose an efficient algorithm that aligns vascular structures and strongly reduces the saw-shaped oscillation, simplifying the inspection of longitudinal cuts; it reduces the motion artifacts caused by the displacement of the catheter in the short-axis plane and the catheter rotation due to vessel tortuosity. The algorithm prototype aligns 3.16 frames/s and clearly outperforms state-of-the-art methods with similar computational cost. The speed of the algorithm is crucial since it allows to inspect the corrected sequence during patient intervention. Moreover, we improved an indirect methodology for IVUS rigid registration algorithm evaluation.
	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	1089-7771	ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ GPL2009			Serial	1250
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	Author	Carlos Martin-Isla; Victor M Campello; Cristian Izquierdo; Kaisar Kushibar; Carla Sendra Balcells; Polyxeni Gkontra; Alireza Sojoudi; Mitchell J Fulton; Tewodros Weldebirhan Arega; Kumaradevan Punithakumar; Lei Li; Xiaowu Sun; Yasmina Al Khalil; Di Liu; Sana Jabbar; Sandro Queiros; Francesco Galati; Moona Mazher; Zheyao Gao; Marcel Beetz; Lennart Tautz; Christoforos Galazis; Marta Varela; Markus Hullebrand; Vicente Grau; Xiahai Zhuang; Domenec Puig; Maria A Zuluaga; Hassan Mohy Ud Din; Dimitris Metaxas; Marcel Breeuwer; Rob J van der Geest; Michelle Noga; Stephanie Bricq; Mark E Rentschler; Andrea Guala; Steffen E Petersen; Sergio Escalera; Jose F Rodriguez Palomares; Karim Lekadir
	Title	Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&ms Challenge			Type	Journal Article
	Year	2023	Publication	IEEE Journal of Biomedical and Health Informatics	Abbreviated Journal	JBHI
	Volume	27	Issue	7	Pages	3302-3313
	Keywords
	Abstract	In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of the right ventricle is challenging due to its highly complex shape and ill-defined borders. Hence, there is a need for new methods to handle such structure's geometrical and textural complexities, notably in the presence of pathologies such as Dilated Right Ventricle, Tricuspid Regurgitation, Arrhythmogenesis, Tetralogy of Fallot, and Inter-atrial Communication. The last MICCAI challenge on right ventricle segmentation was held in 2012 and included only 48 cases from a single clinical center. As part of the 12th Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2021), the M&Ms-2 challenge was organized to promote the interest of the research community around right ventricle segmentation in multi-disease, multi-view, and multi-center cardiac MRI. Three hundred sixty CMR cases, including short-axis and long-axis 4-chamber views, were collected from three Spanish hospitals using nine different scanners from three different vendors, and included a diverse set of right and left ventricle pathologies. The solutions provided by the participants show that nnU-Net achieved the best results overall. However, multi-view approaches were able to capture additional information, highlighting the need to integrate multiple cardiac diseases, views, scanners, and acquisition protocols to produce reliable automatic cardiac segmentation algorithms.
	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	HUPBA			Approved	no
	Call Number	Admin @ si @ MCI2023			Serial	3880
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	Author	Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez
	Title	Rank Estimation in 3D Multibody Motion Segmentation			Type	Journal Article
	Year	2008	Publication	Electronic Letters	Abbreviated Journal
	Volume	44	Issue	4	Pages	279-280
	Keywords
	Abstract	A novel technique for rank estimation in 3D multibody motion segmentation is proposed. It is based on the study of the frequency spectra of moving rigid objects and does not use or assume a prior knowledge of the objects contained in the scene (i.e. number of objects and motion). The significance of rank estimation on multibody motion segmentation results is shown by using two motion segmentation algorithms over both synthetic and real data.
	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	ADAS			Approved	no
	Call Number	ADAS @ adas @ JSL2008a			Serial	939
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