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	Author	Lorenzo Seidenari; Giuseppe Serra; Andrew Bagdanov; Alberto del Bimbo
	Title	Local pyramidal descriptors for image recognition			Type	Journal Article
	Year	2014	Publication	IEEE Transactions on Pattern Analysis and Machine Intelligence	Abbreviated Journal	TPAMI
	Volume	36	Issue	5	Pages	1033 - 1040
	Keywords	Object categorization; local features; kernel methods
	Abstract	In this paper we present a novel method to improve the flexibility of descriptor matching for image recognition by using local multiresolution pyramids in feature space. We propose that image patches be represented at multiple levels of descriptor detail and that these levels be defined in terms of local spatial pooling resolution. Preserving multiple levels of detail in local descriptors is a way of hedging one’s bets on which levels will most relevant for matching during learning and recognition. We introduce the Pyramid SIFT (P-SIFT) descriptor and show that its use in four state-of-the-art image recognition pipelines improves accuracy and yields state-of-the-art results. Our technique is applicable independently of spatial pyramid matching and we show that spatial pyramids can be combined with local pyramids to obtain further improvement.We achieve state-of-the-art results on Caltech-101 (80.1%) and Caltech-256 (52.6%) when compared to other approaches based on SIFT features over intensity images. Our technique is efficient and is extremely easy to integrate into image recognition pipelines.
	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; 600.079			Approved	no
	Call Number	Admin @ si @ SSB2014			Serial	2524
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	Author	Antonio Hernandez; Stan Sclaroff; Sergio Escalera
	Title	Contextual rescoring for Human Pose Estimation			Type	Conference Article
	Year	2014	Publication	25th British Machine Vision Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	A contextual rescoring method is proposed for improving the detection of body joints of a pictorial structure model for human pose estimation. A set of mid-level parts is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body joint hypotheses. A technique is proposed for the automatic discovery of a compact subset of poselets that covers a set of validation images while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for body joint detections, given its relationship to detections of other body joints and mid-level parts in the image. This new score complements the unary potential of a discriminatively trained pictorial structure model. Experiments on two benchmarks show performance improvements when considering the proposed mid-level image representation and rescoring approach in comparison with other pictorial structure-based approaches.
	Address	Nottingham; UK; 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	BMVC
	Notes	HuPBA;MILAB			Approved	no
	Call Number	HSE2014			Serial	2525
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	Author	Cristhian A. Aguilera-Carrasco
	Title	Evaluation of feature detectors and descriptors in VISIBLE-LWIR cross-spectral imaging			Type	Report
	Year	2014	Publication	CVC Technical Report	Abbreviated Journal
	Volume	177	Issue		Pages
	Keywords	Multi-spectral; Cross-spectral; Visible-LWIR imaging; Multimodal.
	Abstract	This thesis evaluates the performance of different state-of-art feature detectors and descriptors algorithms in the Visible-LWIR cross-spectral scenario. The focus is to determine if current detector and descriptor algorithms can be used to match features between the LWIR spectrum and the visible spectrum in applications such as, visual odometry, object recognition, image registration and stereo vision. An outdoor cross-spectral dataset was created to evaluate the suitability of the different algorithms. The results show that the tested algorithms are not suitable to the task of matching features across different spectra. The repeatability ratio was smaller than the 30 percent in the best case and in general matched features were not accurate located. Additionally, these results also suggest that is necessary to create new algorithms that take into account the nature of the different spectra, describing characteristics that exist in both spectra such as discontinuities.
	Address
	Corporate Author				Thesis	Master's 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; 600.076			Approved	no
	Call Number	Admin @ si @Agu2014			Serial	2526
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	Author	Xim Cerda-Company; C. Alejandro Parraga; Xavier Otazu
	Title	Which tone-mapping is the best? A comparative study of tone-mapping perceived quality			Type	Abstract
	Year	2014	Publication	Perception	Abbreviated Journal
	Volume	43	Issue		Pages	106
	Keywords
	Abstract	Perception 43 ECVP Abstract Supplement High-dynamic-range (HDR) imaging refers to the methods designed to increase the brightness dynamic range present in standard digital imaging techniques. This increase is achieved by taking the same picture under dierent exposure values and mapping the intensity levels into a single image by way of a tone-mapping operator (TMO). Currently, there is no agreement on how to evaluate the quality of dierent TMOs. In this work we psychophysically evaluate 15 dierent TMOs obtaining rankings based on the perceived properties of the resulting tone-mapped images. We performed two dierent experiments on a CRT calibrated display using 10 subjects: (1) a study of the internal relationships between grey-levels and (2) a pairwise comparison of the resulting 15 tone-mapped images. In (1) observers internally matched the grey-levels to a reference inside the tone-mapped images and in the real scene. In (2) observers performed a pairwise comparison of the tone-mapped images alongside the real scene. We obtained two rankings of the TMOs according their performance. In (1) the best algorithm was ICAM by J.Kuang et al (2007) and in (2) the best algorithm was a TMO by Krawczyk et al (2005). Our results also show no correlation between these two rankings.
	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	ECVP
	Notes	CIC; NEUROBIT; 600.074			Approved	no
	Call Number	Admin @ si @ CPO2014			Serial	2527
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	Author	Noha Elfiky; Theo Gevers; Arjan Gijsenij; Jordi Gonzalez
	Title	Color Constancy using 3D Scene Geometry derived from a Single Image			Type	Journal Article
	Year	2014	Publication	IEEE Transactions on Image Processing	Abbreviated Journal	TIP
	Volume	23	Issue	9	Pages	3855-3868
	Keywords
	Abstract	The aim of color constancy is to remove the effect of the color of the light source. As color constancy is inherently an ill-posed problem, most of the existing color constancy algorithms are based on specific imaging assumptions (e.g. grey-world and white patch assumption). In this paper, 3D geometry models are used to determine which color constancy method to use for the different geometrical regions (depth/layer) found in images. The aim is to classify images into stages (rough 3D geometry models). According to stage models; images are divided into stage regions using hard and soft segmentation. After that, the best color constancy methods is selected for each geometry depth. To this end, we propose a method to combine color constancy algorithms by investigating the relation between depth, local image statistics and color constancy. Image statistics are then exploited per depth to select the proper color constancy method. Our approach opens the possibility to estimate multiple illuminations by distinguishing nearby light source from distant illuminations. Experiments on state-of-the-art data sets show that the proposed algorithm outperforms state-of-the-art single color constancy algorithms with an improvement of almost 50% of median angular error. When using a perfect classifier (i.e, all of the test images are correctly classified into stages); the performance of the proposed method achieves an improvement of 52% of the median angular error compared to the best-performing single color constancy algorithm.
	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	1057-7149	ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE; 600.078			Approved	no
	Call Number	Admin @ si @ EGG2014			Serial	2528
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	Author	Francisco Cruz; Oriol Ramos Terrades
	Title	EM-Based Layout Analysis Method for Structured Documents			Type	Conference Article
	Year	2014	Publication	22nd International Conference on Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	315-320
	Keywords
	Abstract	In this paper we present a method to perform layout analysis in structured documents. We proposed an EM-based algorithm to fit a set of Gaussian mixtures to the different regions according to the logical distribution along the page. After the convergence, we estimate the final shape of the regions according to the parameters computed for each component of the mixture. We evaluated our method in the task of record detection in a collection of historical structured documents and performed a comparison with other previous works in this task.
	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	1051-4651	ISBN		Medium
	Area		Expedition		Conference	ICPR
	Notes	DAG; 602.006; 600.061; 600.077			Approved	no
	Call Number	Admin @ si @ CrR2014			Serial	2530
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	Author	Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi
	Title	Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars			Type	Journal Article
	Year	2015	Publication	Neurocomputing	Abbreviated Journal	NEUCOM
	Volume	150	Issue	A	Pages	147-154
	Keywords	document image analysis; stochastic context-free grammars; text classication features
	Abstract	In this paper we dene a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents. Two sets of text classication features are used to perform an initial classication of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models and the results showed that the proposed grammatical model outperformed the other methods. Furthermore, grammars also provide the document structure along with its segmentation.
	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; 601.158; 600.077; 600.061			Approved	no
	Call Number	Admin @ si @ ACS2015			Serial	2531
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	Author	Miguel Oliveira; Victor Santos; Angel Sappa
	Title	Multimodal Inverse Perspective Mapping			Type	Journal Article
	Year	2015	Publication	Information Fusion	Abbreviated Journal	IF
	Volume	24	Issue		Pages	108–121
	Keywords	Inverse perspective mapping; Multimodal sensor fusion; Intelligent vehicles
	Abstract	Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints.
	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; 600.055; 600.076			Approved	no
	Call Number	Admin @ si @ OSS2015c			Serial	2532
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	Author	T. Mouats; N. Aouf; Angel Sappa; Cristhian A. Aguilera-Carrasco; Ricardo Toledo
	Title	Multi-Spectral Stereo Odometry			Type	Journal Article
	Year	2015	Publication	IEEE Transactions on Intelligent Transportation Systems	Abbreviated Journal	TITS
	Volume	16	Issue	3	Pages	1210-1224
	Keywords	Egomotion estimation; feature matching; multispectral odometry (MO); optical flow; stereo odometry; thermal imagery
	Abstract	In this paper, we investigate the problem of visual odometry for ground vehicles based on the simultaneous utilization of multispectral cameras. It encompasses a stereo rig composed of an optical (visible) and thermal sensors. The novelty resides in the localization of the cameras as a stereo setup rather than two monocular cameras of different spectrums. To the best of our knowledge, this is the first time such task is attempted. Log-Gabor wavelets at different orientations and scales are used to extract interest points from both images. These are then described using a combination of frequency and spatial information within the local neighborhood. Matches between the pairs of multimodal images are computed using the cosine similarity function based on the descriptors. Pyramidal Lucas–Kanade tracker is also introduced to tackle temporal feature matching within challenging sequences of the data sets. The vehicle egomotion is computed from the triangulated 3-D points corresponding to the matched features. A windowed version of bundle adjustment incorporating Gauss–Newton optimization is utilized for motion estimation. An outlier removal scheme is also included within the framework to deal with outliers. Multispectral data sets were generated and used as test bed. They correspond to real outdoor scenarios captured using our multimodal setup. Finally, detailed results validating the proposed strategy are illustrated.
	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; 600.055; 600.076			Approved	no
	Call Number	Admin @ si @ MAS2015a			Serial	2533
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	Author	Mohammad Rouhani; E. Boyer; Angel Sappa
	Title	Non-Rigid Registration meets Surface Reconstruction			Type	Conference Article
	Year	2014	Publication	International Conference on 3D Vision	Abbreviated Journal
	Volume		Issue		Pages	617-624
	Keywords
	Abstract	Non rigid registration is an important task in computer vision with many applications in shape and motion modeling. A fundamental step of the registration is the data association between the source and the target sets. Such association proves difficult in practice, due to the discrete nature of the information and its corruption by various types of noise, e.g. outliers and missing data. In this paper we investigate the benefit of the implicit representations for the non-rigid registration of 3D point clouds. First, the target points are described with small quadratic patches that are blended through partition of unity weighting. Then, the discrete association between the source and the target can be replaced by a continuous distance field induced by the interface. By combining this distance field with a proper deformation term, the registration energy can be expressed in a linear least square form that is easy and fast to solve. This significantly eases the registration by avoiding direct association between points. Moreover, a hierarchical approach can be easily implemented by employing coarse-to-fine representations. Experimental results are provided for point clouds from multi-view data sets. The qualitative and quantitative comparisons show the outperformance and robustness of our framework. %in presence of noise and outliers.
	Address	Tokyo; Japan; December 2014
	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	3DV
	Notes	ADAS; 600.055; 600.076			Approved	no
	Call Number	Admin @ si @ RBS2014			Serial	2534
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	Author	Lluis Gomez; Dimosthenis Karatzas
	Title	Scene Text Recognition: No Country for Old Men?			Type	Conference Article
	Year	2014	Publication	1st International Workshop on Robust Reading	Abbreviated Journal
	Volume		Issue		Pages
	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	IWRR
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ GoK2014c			Serial	2538
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	Author	E. Bondi ; L. Sidenari; Andrew Bagdanov; Alberto del Bimbo
	Title	Real-time people counting from depth imagery of crowded environments			Type	Conference Article
	Year	2014	Publication	11th IEEE International Conference on Advanced Video and Signal based Surveillance	Abbreviated Journal
	Volume		Issue		Pages	337 - 342
	Keywords
	Abstract	In this paper we describe a system for automatic people counting in crowded environments. The approach we propose is a counting-by-detection method based on depth imagery. It is designed to be deployed as an autonomous appliance for crowd analysis in video surveillance application scenarios. Our system performs foreground/background segmentation on depth image streams in order to coarsely segment persons, then depth information is used to localize head candidates which are then tracked in time on an automatically estimated ground plane. The system runs in real-time, at a frame-rate of about 20 fps. We collected a dataset of RGB-D sequences representing three typical and challenging surveillance scenarios, including crowds, queuing and groups. An extensive comparative evaluation is given between our system and more complex, Latent SVM-based head localization for person counting applications.
	Address	Seoul; Korea; August 2014
	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	AVSS
	Notes	LAMP; 600.079			Approved	no
	Call Number	Admin @ si @ BSB2014			Serial	2540
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	Author	Mohammad Rouhani; Angel Sappa; E. Boyer
	Title	Implicit B-Spline Surface Reconstruction			Type	Journal Article
	Year	2015	Publication	IEEE Transactions on Image Processing	Abbreviated Journal	TIP
	Volume	24	Issue	1	Pages	22 - 32
	Keywords
	Abstract	This paper presents a fast and flexible curve, and surface reconstruction technique based on implicit B-spline. This representation does not require any parameterization and it is locally supported. This fact has been exploited in this paper to propose a reconstruction technique through solving a sparse system of equations. This method is further accelerated to reduce the dimension to the active control lattice. Moreover, the surface smoothness and user interaction are allowed for controlling the surface. Finally, a novel weighting technique has been introduced in order to blend small patches and smooth them in the overlapping regions. The whole framework is very fast and efficient and can handle large cloud of points with very low computational cost. The experimental results show the flexibility and accuracy of the proposed algorithm to describe objects with complex topologies. Comparisons with other fitting methods highlight the superiority of the proposed approach in the presence of noise and missing 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	1057-7149	ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS; 600.076			Approved	no
	Call Number	Admin @ si @ RSB2015			Serial	2541
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	Author	Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
	Title	Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors			Type	Conference Article
	Year	2014	Publication	11th IAPR International Workshop on Document Analysis and Systems	Abbreviated Journal
	Volume		Issue		Pages	156-160
	Keywords
	Abstract	This paper proposes a new approach to spot symbols into graphical documents using sparse representations. More specifically, a dictionary is learned from a training database of local descriptors defined over the documents. Following their sparse representations, interest points sharing similar properties are used to define interest regions. Using an original adaptation of information retrieval techniques, a vector model for interest regions and for a query symbol is built based on its sparsity in a visual vocabulary where the visual words are columns in the learned dictionary. The matching process is performed comparing the similarity between vector models. Evaluation on SESYD datasets demonstrates that our method is promising.
	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	978-1-4799-3243-6	Medium
	Area		Expedition		Conference	DAS
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ DTR2014			Serial	2543
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	Author	Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados
	Title	Efficient segmentation-free keyword spotting in historical document collections			Type	Journal Article
	Year	2015	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	48	Issue	2	Pages	545–555
	Keywords	Historical documents; Keyword spotting; Segmentation-free; Dense SIFT features; Latent semantic analysis; Product quantization
	Abstract	In this paper we present an efficient segmentation-free word spotting method, applied in the context of historical document collections, that follows the query-by-example paradigm. We use a patch-based framework where local patches are described by a bag-of-visual-words model powered by SIFT descriptors. By projecting the patch descriptors to a topic space with the latent semantic analysis technique and compressing the descriptors with the product quantization method, we are able to efficiently index the document information both in terms of memory and time. The proposed method is evaluated using four different collections of historical documents achieving good performances on both handwritten and typewritten scenarios. The yielded performances outperform the recent state-of-the-art keyword spotting approaches.
	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; ADAS; 600.076; 600.077; 600.061; 601.223; 602.006; 600.055			Approved	no
	Call Number	Admin @ si @ RAT2015a			Serial	2544
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