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Author Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez
Title Solving the Multi Object Occlusion Problem in a Multiple Camera Tracking System Type Journal
Year 2009 Publication Pattern Recognition and Image Analysis Abbreviated Journal
Volume 19 Issue 1 Pages 165-171
Keywords
Abstract An efficient method to overcome adverse effects of occlusion upon object tracking is presented. The method is based on matching paths of objects in time and solves a complex occlusion-caused problem of merging separate segments of the same path.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 1054-6618 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ MAR2009a Serial 1160
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Author Joost Van de Weijer; Cordelia Schmid; Jakob Verbeek; Diane Larlus
Title Learning Color Names for Real-World Applications Type Journal Article
Year 2009 Publication IEEE Transaction in Image Processing Abbreviated Journal TIP
Volume 18 Issue 7 Pages 1512–1524
Keywords
Abstract Color names are required in real-world applications such as image retrieval and image annotation. Traditionally, they are learned from a collection of labelled color chips. These color chips are labelled with color names within a well-defined experimental setup by human test subjects. However naming colors in real-world images differs significantly from this experimental setting. In this paper, we investigate how color names learned from color chips compare to color names learned from real-world images. To avoid hand labelling real-world images with color names we use Google Image to collect a data set. Due to limitations of Google Image this data set contains a substantial quantity of wrongly labelled data. We propose several variants of the PLSA model to learn color names from this noisy data. Experimental results show that color names learned from real-world images significantly outperform color names learned from labelled color chips for both image retrieval and image annotation.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number CAT @ cat @ WSV2009 Serial 1195
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Author Ariel Amato; Mikhail Mozerov; Andrew Bagdanov; Jordi Gonzalez
Title Accurate Moving Cast Shadow Suppression Based on Local Color Constancy detection Type Journal Article
Year 2011 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 20 Issue 10 Pages 2954 - 2966
Keywords
Abstract This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ AMB2011 Serial 1716
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Author Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
Title Computational Color Constancy: Survey and Experiments Type Journal Article
Year 2011 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 20 Issue 9 Pages 2475-2489
Keywords computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting
Abstract Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ISE;CIC Approved no
Call Number Admin @ si @ GGW2011 Serial 1717
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Author Mohammad Rouhani; Angel Sappa
Title Implicit Polynomial Representation through a Fast Fitting Error Estimation Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 4 Pages 2089-2098
Keywords
Abstract Impact Factor
This paper presents a simple distance estimation for implicit polynomial fitting. It is computed as the height of a simplex built between the point and the surface (i.e., a triangle in 2-D or a tetrahedron in 3-D), which is used as a coarse but reliable estimation of the orthogonal distance. The proposed distance can be described as a function of the coefficients of the implicit polynomial. Moreover, it is differentiable and has a smooth behavior . Hence, it can be used in any gradient-based optimization. In this paper, its use in a Levenberg-Marquardt framework is shown, which is particularly devoted for nonlinear least squares problems. The proposed estimation is a generalization of the gradient-based distance estimation, which is widely used in the literature. Experimental results, both in 2-D and 3-D data sets, are provided. Comparisons with state-of-the-art techniques are presented, showing the advantages of the proposed approach.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ RoS2012b; ADAS @ adas @ Serial 1937
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Author J. Stöttinger; A. Hanbury; N. Sebe; Theo Gevers
Title Spars Color Interest Points for Image Retrieval and Object Categorization Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 5 Pages 2681-2692
Keywords
Abstract Impact factor 2010: 2.92
IF 2011/2012?: 3.32
Interest point detection is an important research area in the field of image processing and computer vision. In particular, image retrieval and object categorization heavily rely on interest point detection from which local image descriptors are computed for image matching. In general, interest points are based on luminance, and color has been largely ignored. However, the use of color increases the distinctiveness of interest points. The use of color may therefore provide selective search reducing the total number of interest points used for image matching. This paper proposes color interest points for sparse image representation. To reduce the sensitivity to varying imaging conditions, light-invariant interest points are introduced. Color statistics based on occurrence probability lead to color boosted points, which are obtained through saliency-based feature selection. Furthermore, a principal component analysis-based scale selection method is proposed, which gives a robust scale estimation per interest point. From large-scale experiments, it is shown that the proposed color interest point detector has higher repeatability than a luminance-based one. Furthermore, in the context of image retrieval, a reduced and predictable number of color features show an increase in performance compared to state-of-the-art interest points. Finally, in the context of object recognition, for the Pascal VOC 2007 challenge, our method gives comparable performance to state-of-the-art methods using only a small fraction of the features, reducing the computing time considerably.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
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Notes ALTRES;ISE Approved no
Call Number Admin @ si @ SHS2012 Serial 1847
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Author R. Valenti; Theo Gevers
Title Combining Head Pose and Eye Location Information for Gaze Estimation Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 2 Pages 802-815
Keywords
Abstract Impact factor 2010: 2.92
Impact factor 2011/12?: 3.32
Head pose and eye location for gaze estimation have been separately studied in numerous works in the literature. Previous research shows that satisfactory accuracy in head pose and eye location estimation can be achieved in constrained settings. However, in the presence of nonfrontal faces, eye locators are not adequate to accurately locate the center of the eyes. On the other hand, head pose estimation techniques are able to deal with these conditions; hence, they may be suited to enhance the accuracy of eye localization. Therefore, in this paper, a hybrid scheme is proposed to combine head pose and eye location information to obtain enhanced gaze estimation. To this end, the transformation matrix obtained from the head pose is used to normalize the eye regions, and in turn, the transformation matrix generated by the found eye location is used to correct the pose estimation procedure. The scheme is designed to enhance the accuracy of eye location estimations, particularly in low-resolution videos, to extend the operative range of the eye locators, and to improve the accuracy of the head pose tracker. These enhanced estimations are then combined to obtain a novel visual gaze estimation system, which uses both eye location and head information to refine the gaze estimates. From the experimental results, it can be derived that the proposed unified scheme improves the accuracy of eye estimations by 16% to 23%. Furthermore, it considerably extends its operating range by more than 15° by overcoming the problems introduced by extreme head poses. Moreover, the accuracy of the head pose tracker is improved by 12% to 24%. Finally, the experimentation on the proposed combined gaze estimation system shows that it is accurate (with a mean error between 2° and 5°) and that it can be used in cases where classic approaches would fail without imposing restraints on the position of the head.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ VaG 2012b Serial 1851
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Author Arjan Gijsenij; R. Lu; Theo Gevers; De Xu
Title Color Constancy for Multiple Light Source Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 2 Pages 697-707
Keywords
Abstract Impact factor 2010: 2.92
Impact factor 2011/2012?: 3.32
Color constancy algorithms are generally based on the simplifying assumption that the spectral distribution of a light source is uniform across scenes. However, in reality, this assumption is often violated due to the presence of multiple light sources. In this paper, we will address more realistic scenarios where the uniform light-source assumption is too restrictive. First, a methodology is proposed to extend existing algorithms by applying color constancy locally to image patches, rather than globally to the entire image. After local (patch-based) illuminant estimation, these estimates are combined into more robust estimations, and a local correction is applied based on a modified diagonal model. Quantitative and qualitative experiments on spectral and real images show that the proposed methodology reduces the influence of two light sources simultaneously present in one scene. If the chromatic difference between these two illuminants is more than 1° , the proposed framework outperforms algorithms based on the uniform light-source assumption (with error-reduction up to approximately 30%). Otherwise, when the chromatic difference is less than 1° and the scene can be considered to contain one (approximately) uniform light source, the performance of the proposed method framework is similar to global color constancy methods.
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Publisher Place of Publication Editor
Language Summary Language Original Title
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ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ GLG2012a Serial 1852
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Author Hamdi Dibeklioglu; Albert Ali Salah; Theo Gevers
Title A Statistical Method for 2D Facial Landmarking Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 2 Pages 844-858
Keywords
Abstract IF = 3.32
Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in coarse-to-fine fashion and complemented with a shape prior. We assess the accuracy and the robustness of the proposed approach in extensive cross-database conditions conducted on four face data sets (Face Recognition Grand Challenge, Cohn-Kanade, Bosphorus, and BioID). Our method has 99.33% accuracy on the Bosphorus database and 97.62% accuracy on the BioID database on the average, which improves the state of the art. We show that the method is not significantly affected by low-resolution images, small rotations, facial expressions, and natural occlusions such as beard and mustache. We further test the goodness of the landmarks in a facial expression recognition application and report landmarking-induced improvement over baseline on two separate databases for video-based expression recognition (Cohn-Kanade and BU-4DFE).
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ DSG 2012 Serial 1853
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Author Javier Vazquez; Maria Vanrell; Ramon Baldrich; Francesc Tous
Title Color Constancy by Category Correlation Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 4 Pages 1997-2007
Keywords
Abstract Finding color representations which are stable to illuminant changes is still an open problem in computer vision. Until now most approaches have been based on physical constraints or statistical assumptions derived from the scene, while very little attention has been paid to the effects that selected illuminants have
on the final color image representation. The novelty of this work is to propose
perceptual constraints that are computed on the corrected images. We define the
category hypothesis, which weights the set of feasible illuminants according to their ability to map the corrected image onto specific colors. Here we choose these colors as the universal color categories related to basic linguistic terms which have been psychophysically measured. These color categories encode natural color statistics, and their relevance across different cultures is indicated by the fact that they have received a common color name. From this category hypothesis we propose a fast implementation that allows the sampling of a large set of illuminants. Experiments prove that our method rivals current state-of-art performance without the need for training algorithmic parameters. Additionally, the method can be used as a framework to insert top-down information from other sources, thus opening further research directions in solving for color constancy.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
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Notes CIC Approved no
Call Number Admin @ si @ VVB2012 Serial 1999
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Author Mikhail Mozerov
Title Constrained Optical Flow Estimation as a Matching Problem Type Journal Article
Year 2013 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 22 Issue 5 Pages 2044-2055
Keywords
Abstract In general, discretization in the motion vector domain yields an intractable number of labels. In this paper we propose an approach that can reduce general optical flow to the constrained matching problem by pre-estimating a 2D disparity labeling map of the desired discrete motion vector function. One of the goals of the proposed paper is estimating coarse distribution of motion vectors and then utilizing this distribution as global constraints for discrete optical flow estimation. This pre-estimation is done with a simple frame-to-frame correlation technique also known as the digital symmetric-phase-only-filter (SPOF). We discover a strong correlation between the output of the SPOF and the motion vector distribution of the related optical flow. The two step matching paradigm for optical flow estimation is applied: pixel accuracy (integer flow), and subpixel accuracy estimation. The matching problem is solved by global optimization. Experiments on the Middlebury optical flow datasets confirm our intuitive assumptions about strong correlation between motion vector distribution of optical flow and maximal peaks of SPOF outputs. The overall performance of the proposed method is promising and achieves state-of-the-art results on the Middlebury benchmark.
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Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
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Notes ISE Approved no
Call Number Admin @ si @ Moz2013 Serial 2191
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Author Shida Beigpour; Christian Riess; Joost Van de Weijer; Elli Angelopoulou
Title Multi-Illuminant Estimation with Conditional Random Fields Type Journal Article
Year 2014 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 23 Issue 1 Pages 83-95
Keywords color constancy; CRF; multi-illuminant
Abstract Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over a set of local illuminant estimates. In order to quantitatively evaluate the proposed method, we created a novel data set of two-dominant-illuminant images comprised of laboratory, indoor, and outdoor scenes. Unlike prior work, our database includes accurate pixel-wise ground truth illuminant information. The performance of our method is evaluated on multiple data sets. Experimental results show that our framework clearly outperforms single illuminant estimators as well as a recently proposed multi-illuminant estimation approach.
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ISSN (up) 1057-7149 ISBN Medium
Area Expedition Conference
Notes CIC; LAMP; 600.074; 600.079 Approved no
Call Number Admin @ si @ BRW2014 Serial 2451
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Author Fahad Shahbaz Khan; Joost Van de Weijer; Muhammad Anwer Rao; Michael Felsberg; Carlo Gatta
Title Semantic Pyramids for Gender and Action Recognition Type Journal Article
Year 2014 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 23 Issue 8 Pages 3633-3645
Keywords
Abstract Person description is a challenging problem in computer vision. We investigated two major aspects of person description: 1) gender and 2) action recognition in still images. Most state-of-the-art approaches for gender and action recognition rely on the description of a single body part, such as face or full-body. However, relying on a single body part is suboptimal due to significant variations in scale, viewpoint, and pose in real-world images. This paper proposes a semantic pyramid approach for pose normalization. Our approach is fully automatic and based on combining information from full-body, upper-body, and face regions for gender and action recognition in still images. The proposed approach does not require any annotations for upper-body and face of a person. Instead, we rely on pretrained state-of-the-art upper-body and face detectors to automatically extract semantic information of a person. Given multiple bounding boxes from each body part detector, we then propose a simple method to select the best candidate bounding box, which is used for feature extraction. Finally, the extracted features from the full-body, upper-body, and face regions are combined into a single representation for classification. To validate the proposed approach for gender recognition, experiments are performed on three large data sets namely: 1) human attribute; 2) head-shoulder; and 3) proxemics. For action recognition, we perform experiments on four data sets most used for benchmarking action recognition in still images: 1) Sports; 2) Willow; 3) PASCAL VOC 2010; and 4) Stanford-40. Our experiments clearly demonstrate that the proposed approach, despite its simplicity, outperforms state-of-the-art methods for gender and action recognition.
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ISSN (up) 1057-7149 ISBN Medium
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Notes CIC; LAMP; 601.160; 600.074; 600.079;MILAB Approved no
Call Number Admin @ si @ KWR2014 Serial 2507
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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.
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ISSN (up) 1057-7149 ISBN Medium
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Notes ISE; 600.078 Approved no
Call Number Admin @ si @ EGG2014 Serial 2528
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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.
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Series Editor Series Title Abbreviated Series Title
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ISSN (up) 1057-7149 ISBN Medium
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Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ RSB2015 Serial 2541
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