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Author | A. Toet; M. Henselmans; M.P. Lucassen; Theo Gevers | ||||
Title | Emotional effects of dynamic textures | Type | Journal | ||
Year | 2011 | Publication | i-Perception | Abbreviated Journal | iPER |
Volume | 2 | Issue ![]() |
9 | Pages | 969 – 991 |
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Abstract | This study explores the effects of various spatiotemporal dynamic texture characteristics on human emotions. The emotional experience of auditory (eg, music) and haptic repetitive patterns has been studied extensively. In contrast, the emotional experience of visual dynamic textures is still largely unknown, despite their natural ubiquity and increasing use in digital media. Participants watched a set of dynamic textures, representing either water or various different media, and self-reported their emotional experience. Motion complexity was found to have mildly relaxing and nondominant effects. In contrast, motion change complexity was found to be arousing and dominant. The speed of dynamics had arousing, dominant, and unpleasant effects. The amplitude of dynamics was also regarded as unpleasant. The regularity of the dynamics over the textures’ area was found to be uninteresting, nondominant, mildly relaxing, and mildly pleasant. The spatial scale of the dynamics had an unpleasant, arousing, and dominant effect, which was larger for textures with diverse content than for water textures. For water textures, the effects of spatial contrast were arousing, dominant, interesting, and mildly unpleasant. None of these effects were observed for textures of diverse content. The current findings are relevant for the design and synthesis of affective multimedia content and for affective scene indexing and retrieval. | ||||
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ISSN | 2041-6695 | ISBN | Medium | ||
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Notes | ALTRES;ISE | Approved | no | ||
Call Number | Admin @ si @THL2011 | Serial | 1843 | ||
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Author | Koen E.A. van de Sande; Theo Gevers; C.G.M. Snoek | ||||
Title | Evaluating Color Descriptors for Object and Scene Recognition | Type | Journal Article | ||
Year | 2010 | Publication | IEEE Transaction on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 32 | Issue ![]() |
9 | Pages | 1582 - 1596 |
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Abstract | Impact factor: 5.308
Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge. |
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Series Volume | Series Issue | Edition | |||
ISSN | 0162-8828 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ALTRES;ISE | Approved | no | ||
Call Number | Admin @ si @ SGS2010 | Serial | 1846 | ||
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Author | R. Valenti; Theo Gevers | ||||
Title | Accurate Eye Center Location through Invariant Isocentric Patterns | Type | Journal Article | ||
Year | 2012 | Publication | IEEE Transaction on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 34 | Issue ![]() |
9 | Pages | 1785-1798 |
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Abstract | Impact factor 2010: 5.308
Impact factor 2011/12?: 5.96 Locating the center of the eyes allows for valuable information to be captured and used in a wide range of applications. Accurate eye center location can be determined using commercial eye-gaze trackers, but additional constraints and expensive hardware make these existing solutions unattractive and impossible to use on standard (i.e., visible wavelength), low-resolution images of eyes. Systems based solely on appearance are proposed in the literature, but their accuracy does not allow us to accurately locate and distinguish eye centers movements in these low-resolution settings. Our aim is to bridge this gap by locating the center of the eye within the area of the pupil on low-resolution images taken from a webcam or a similar device. The proposed method makes use of isophote properties to gain invariance to linear lighting changes (contrast and brightness), to achieve in-plane rotational invariance, and to keep low-computational costs. To further gain scale invariance, the approach is applied to a scale space pyramid. In this paper, we extensively test our approach for its robustness to changes in illumination, head pose, scale, occlusion, and eye rotation. We demonstrate that our system can achieve a significant improvement in accuracy over state-of-the-art techniques for eye center location in standard low-resolution imagery. |
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Series Volume | Series Issue | Edition | |||
ISSN | 0162-8828 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ALTRES;ISE | Approved | no | ||
Call Number | Admin @ si @ VaG 2012a | Serial | 1849 | ||
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Author | Jon Almazan; Alicia Fornes; Ernest Valveny | ||||
Title | A non-rigid appearance model for shape description and recognition | Type | Journal Article | ||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 45 | Issue ![]() |
9 | Pages | 3105--3113 |
Keywords | Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition | ||||
Abstract | In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach. | ||||
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ISSN | 0031-3203 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ AFV2012 | Serial | 1982 | ||
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Author | Jaume Gibert; Ernest Valveny; Horst Bunke | ||||
Title | Graph Embedding in Vector Spaces by Node Attribute Statistics | Type | Journal Article | ||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 45 | Issue ![]() |
9 | Pages | 3072-3083 |
Keywords | Structural pattern recognition; Graph embedding; Data clustering; Graph classification | ||||
Abstract | Graph-based representations are of broad use and applicability in pattern recognition. They exhibit, however, a major drawback with regards to the processing tools that are available in their domain. Graphembedding into vectorspaces is a growing field among the structural pattern recognition community which aims at providing a feature vector representation for every graph, and thus enables classical statistical learning machinery to be used on graph-based input patterns. In this work, we propose a novel embedding methodology for graphs with continuous nodeattributes and unattributed edges. The approach presented in this paper is based on statistics of the node labels and the edges between them, based on their similarity to a set of representatives. We specifically deal with an important issue of this methodology, namely, the selection of a suitable set of representatives. In an experimental evaluation, we empirically show the advantages of this novel approach in the context of different classification problems using several databases of graphs. | ||||
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ISSN | 0031-3203 | ISBN | Medium | ||
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ GVB2012a | Serial | 1992 | ||
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Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
Title | Towards Automatic Polyp Detection with a Polyp Appearance Model | Type | Journal Article | ||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 45 | Issue ![]() |
9 | Pages | 3166-3182 |
Keywords | Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot | ||||
Abstract | This work aims at the automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region. The output of the algorithm also defines which regions can be considered as non-informative. We define as our region descriptor the novel Sector Accumulation-Depth of Valleys Accumulation (SA-DOVA), which provides a necessary but not sufficient condition for the polyp presence. Finally, we classify our segmented regions according to the maximal values of the SA-DOVA descriptor. Our preliminary classification results are promising, especially when classifying those parts of the image that do not contain a polyp inside. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | 0031-3203 | ISBN | Medium | ||
Area | 800 | Expedition | Conference | IbPRIA | |
Notes | MV;SIAI | Approved | no | ||
Call Number | Admin @ si @ BSV2012; IAM @ iam | Serial | 1997 | ||
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Author | Mario Hernandez; Joao Sanchez; Jordi Vitria | ||||
Title | Selected papers from Iberian Conference on Pattern Recognition and Image Analysis | Type | Book Whole | ||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | |
Volume | 45 | Issue ![]() |
9 | Pages | 3047-3582 |
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ISSN | 0031-3203 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ HSV2012 | Serial | 2069 | ||
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Author | Miguel Reyes; Albert Clapes; Jose Ramirez; Juan R Revilla; Sergio Escalera | ||||
Title | Automatic Digital Biometry Analysis based on Depth Maps | Type | Journal Article | ||
Year | 2013 | Publication | Computers in Industry | Abbreviated Journal | COMPUTIND |
Volume | 64 | Issue ![]() |
9 | Pages | 1316-1325 |
Keywords | Multi-modal data fusion; Depth maps; Posture analysis; Anthropometric data; Musculo-skeletal disorders; Gesture analysis | ||||
Abstract | World Health Organization estimates that 80% of the world population is affected by back-related disorders during his life. Current practices to analyze musculo-skeletal disorders (MSDs) are expensive, subjective, and invasive. In this work, we propose a tool for static body posture analysis and dynamic range of movement estimation of the skeleton joints based on 3D anthropometric information from multi-modal data. Given a set of keypoints, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matched, and accurate measurements about posture and spinal curvature are computed. Given a set of joints, range of movement measurements is also obtained. Moreover, gesture recognition based on joint movements is performed to look for the correctness in the development of physical exercises. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent MSDs, as well as tracking the posture evolution of patients in rehabilitation treatments. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
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Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RCR2013 | Serial | 2252 | ||
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Author | Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
Title | Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation | Type | Journal Article | ||
Year | 2013 | Publication | Ultrasound in Medicine and Biology | Abbreviated Journal | UMB |
Volume | 39 | Issue ![]() |
9 | Pages | 1698-712 |
Keywords | Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy | ||||
Abstract | Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages. | ||||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ ABC2013 | Serial | 2313 | ||
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Author | Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo | ||||
Title | Multispectral Image Feature Points | Type | Journal Article | ||
Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 12 | Issue ![]() |
9 | Pages | 12661-12672 |
Keywords | multispectral image descriptor; color and infrared images; feature point descriptor | ||||
Abstract | Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. | ||||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ ABL2012 | Serial | 2154 | ||
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Author | Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco | ||||
Title | Brightness induction by contextual influences in V1: a neurodynamical account | Type | Abstract | ||
Year | 2012 | Publication | Journal of Vision | Abbreviated Journal | VSS |
Volume | 12 | Issue ![]() |
9 | Pages | |
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Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas and reveals fundamental properties of neural organization in the visual system. Several phenomenological models have been proposed that successfully account for psychophysical data (Pessoa et al. 1995, Blakeslee and McCourt 2004, Barkan et al. 2008, Otazu et al. 2008).
Neurophysiological evidence suggests that brightness information is explicitly represented in V1 and neuronal response modulations have been observed followingluminance changes outside their receptive fields (Rossi and Paradiso, 1999). In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (1999) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2–3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as contour detection and preattentive segmentation, which share with brightness induction the relevant effect of contextual influences. In our model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition which makes it possible to recover an image reflecting the perceived intensity. The proposed model successfully accounts for well known pyschophysical effects (among them: the White's and modified White's effects, the Todorović, Chevreul, achromatic ring patterns, and grating induction effects). Our work suggests that intra-cortical interactions in the primary visual cortex could partially explain perceptual brightness induction effects and reveals how a common general architecture may account for several different fundamental processes emerging early in the visual pathway. |
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ OPD2012b | Serial | 2178 | ||
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Author | Mirko Arnold; Anarta Ghosh; Stephen Ameling; G Lacey | ||||
Title | Automatic segmentation and inpainting of specular highlights for endoscopic imaging | Type | Journal Article | ||
Year | 2010 | Publication | EURASIP Journal on Image and Video Processing | Abbreviated Journal | EURASIP JIVP |
Volume | 2010 | Issue ![]() |
9 | Pages | |
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Area | 800 | Expedition | Conference | ||
Notes | MV | Approved | no | ||
Call Number | fernando @ fernando @ | Serial | 2423 | ||
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Author | Naveen Onkarappa; Angel Sappa | ||||
Title | Synthetic sequences and ground-truth flow field generation for algorithm validation | Type | Journal Article | ||
Year | 2015 | Publication | Multimedia Tools and Applications | Abbreviated Journal | MTAP |
Volume | 74 | Issue ![]() |
9 | Pages | 3121-3135 |
Keywords | Ground-truth optical flow; Synthetic sequence; Algorithm validation | ||||
Abstract | Research in computer vision is advancing by the availability of good datasets that help to improve algorithms, validate results and obtain comparative analysis. The datasets can be real or synthetic. For some of the computer vision problems such as optical flow it is not possible to obtain ground-truth optical flow with high accuracy in natural outdoor real scenarios directly by any sensor, although it is possible to obtain ground-truth data of real scenarios in a laboratory setup with limited motion. In this difficult situation computer graphics offers a viable option for creating realistic virtual scenarios. In the current work we present a framework to design virtual scenes and generate sequences as well as ground-truth flow fields. Particularly, we generate a dataset containing sequences of driving scenarios. The sequences in the dataset vary in different speeds of the on-board vision system, different road textures, complex motion of vehicle and independent moving vehicles in the scene. This dataset enables analyzing and adaptation of existing optical flow methods, and leads to invention of new approaches particularly for driver assistance systems. | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
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ISSN | 1380-7501 | ISBN | Medium | ||
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Notes | ADAS; 600.055; 601.215; 600.076 | Approved | no | ||
Call Number | Admin @ si @ OnS2014b | Serial | 2472 | ||
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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 |
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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 | 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 | Xavier Otazu; Olivier Penacchio; Xim Cerda-Company | ||||
Title | Brightness and colour induction through contextual influences in V1 | Type | Conference Article | ||
Year | 2015 | Publication | Scottish Vision Group 2015 SGV2015 | Abbreviated Journal | |
Volume | 12 | Issue ![]() |
9 | Pages | 1208-2012 |
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Address | Carnoustie; Scotland; March 2015 | ||||
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Area | Expedition | Conference | SGV | ||
Notes | NEUROBIT; | Approved | no | ||
Call Number | Admin @ si @ OPC2015a | Serial | 2632 | ||
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