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| Author | Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu | ||||
| Title | Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
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12 | Issue | 2 | Pages | 1702-1719 |
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| Abstract | IF=1.77 (2010)
Social interactions are a very important component in peopleís lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Timesí Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network. |
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| Publisher | Molecular Diversity Preservation International | Place of Publication | Editor | ||
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| Notes | MILAB; OR;HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ EBV2012 | Serial | 1885 | ||
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| Author | Javier Vazquez; J. Kevin O'Regan; Maria Vanrell; Graham D. Finlayson | ||||
| Title | A new spectrally sharpened basis to predict colour naming, unique hues, and hue cancellation | Type | Journal Article | ||
| Year | 2012 | Publication | Journal of Vision | Abbreviated Journal | VSS |
| Volume |
12 | Issue | 6 (7) | Pages | 1-14 |
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| Abstract | When light is reflected off a surface, there is a linear relation between the three human photoreceptor responses to the incoming light and the three photoreceptor responses to the reflected light. Different colored surfaces have different linear relations. Recently, Philipona and O'Regan (2006) showed that when this relation is singular in a mathematical sense, then the surface is perceived as having a highly nameable color. Furthermore, white light reflected by that surface is perceived as corresponding precisely to one of the four psychophysically measured unique hues. However, Philipona and O'Regan's approach seems unrelated to classical psychophysical models of color constancy. In this paper we make this link. We begin by transforming cone sensors to spectrally sharpened counterparts. In sharp color space, illumination change can be modeled by simple von Kries type scalings of response values within each of the spectrally sharpened response channels. In this space, Philipona and O'Regan's linear relation is captured by a simple Land-type color designator defined by dividing reflected light by incident light. This link between Philipona and O'Regan's theory and Land's notion of color designator gives the model biological plausibility. We then show that Philipona and O'Regan's singular surfaces are surfaces which are very close to activating only one or only two of such newly defined spectrally sharpened sensors, instead of the usual three. Closeness to zero is quantified in a new simplified measure of singularity which is also shown to relate to the chromaticness of colors. As in Philipona and O'Regan's original work, our new theory accounts for a large variety of psychophysical color data. | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ VOV2012 | Serial | 1998 | ||
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| Author | Antonio Hernandez; Miguel Reyes; Victor Ponce; Sergio Escalera | ||||
| Title | GrabCut-Based Human Segmentation in Video Sequences | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume |
12 | Issue | 11 | Pages | 15376-15393 |
| Keywords | segmentation; human pose recovery; GrabCut; GraphCut; Active Appearance Models; Conditional Random Field | ||||
| Abstract | In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ HRP2012 | Serial | 2147 | ||
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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 | Cesar Isaza; Joaquin Salas; Bogdan Raducanu | ||||
| Title | Evaluation of Intrinsic Image Algorithms to Detect the Shadows Cast by Static Objects Outdoors | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume |
12 | Issue | 10 | Pages | 13333-13348 |
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| Abstract | In some automatic scene analysis applications, the presence of shadows becomes a nuisance that is necessary to deal with. As a consequence, a preliminary stage in many computer vision algorithms is to attenuate their effect. In this paper, we focus our attention on the detection of shadows cast by static objects outdoors, as the scene is viewed for extended periods of time (days, weeks) from a fixed camera and considering daylight intervals where the main source of light is the sun. In this context, we report two contributions. First, we introduce the use of synthetic images for which ground truth can be generated automatically, avoiding the tedious effort of manual annotation. Secondly, we report a novel application of the intrinsic image concept to the automatic detection of shadows cast by static objects in outdoors. We make both a quantitative and a qualitative evaluation of several algorithms based on this image representation. For the quantitative evaluation, we used the synthetic data set, while for the qualitative evaluation we used both data sets. Our experimental results show that the evaluated methods can partially solve the problem of shadow detection. | ||||
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ ISR2012b | Serial | 2173 | ||
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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 | Jose Carlos Rubio; Joan Serrat; Antonio Lopez; Daniel Ponsa | ||||
| Title | Multiple target tracking for intelligent headlights control | Type | Journal Article | ||
| Year | 2012 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
| Volume |
13 | Issue | 2 | Pages | 594-605 |
| Keywords | Intelligent Headlights | ||||
| Abstract | Intelligent vehicle lighting systems aim at automatically regulating the headlights' beam to illuminate as much of the road ahead as possible while avoiding dazzling other drivers. A key component of such a system is computer vision software that is able to distinguish blobs due to vehicles' headlights and rear lights from those due to road lamps and reflective elements such as poles and traffic signs. In a previous work, we have devised a set of specialized supervised classifiers to make such decisions based on blob features related to its intensity and shape. Despite the overall good performance, there remain challenging that have yet to be solved: notably, faint and tiny blobs corresponding to quite distant vehicles. In fact, for such distant blobs, classification decisions can be taken after observing them during a few frames. Hence, incorporating tracking could improve the overall lighting system performance by enforcing the temporal consistency of the classifier decision. Accordingly, this paper focuses on the problem of constructing blob tracks, which is actually one of multiple-target tracking (MTT), but under two special conditions: We have to deal with frequent occlusions, as well as blob splits and merges. We approach it in a novel way by formulating the problem as a maximum a posteriori inference on a Markov random field. The qualitative (in video form) and quantitative evaluation of our new MTT method shows good tracking results. In addition, we will also see that the classification performance of the problematic blobs improves due to the proposed MTT algorithm. | ||||
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| ISSN | 1524-9050 | ISBN | Medium | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RLP2012; ADAS @ adas @ rsl2012g | Serial | 1877 | ||
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| Author | Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados | ||||
| Title | CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal | Type | Journal Article | ||
| Year | 2012 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume |
15 | Issue | 3 | Pages | 243-251 |
| Keywords | Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths | ||||
| Abstract | 0,405JCR
The analysis of music scores has been an active research field in the last decades. However, there are no publicly available databases of handwritten music scores for the research community. In this paper we present the CVC-MUSCIMA database and ground-truth of handwritten music score images. The dataset consists of 1,000 music sheets written by 50 different musicians. It has been especially designed for writer identification and staff removal tasks. In addition to the description of the dataset, ground-truth, partitioning and evaluation metrics, we also provide some base-line results for easing the comparison between different approaches. |
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ FDG2012 | Serial | 2129 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
| Title | Text line extraction in graphical documents using background and foreground | Type | Journal Article | ||
| Year | 2012 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume |
15 | Issue | 3 | Pages | 227-241 |
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| Abstract | 0,405 JCR
In graphical documents (e.g., maps, engineering drawings), artistic documents etc., the text lines are annotated in multiple orientations or curvilinear way to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted. In this paper, we propose a novel method to segment such text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. In the proposed scheme, at first, individual components are detected and grouped into character clusters in a hierarchical way using size and positional information. Next, the clusters are extended in two extreme sides to determine potential candidate regions. Finally, with the help of these candidate regions, individual lines are extracted. The experimental results are presented on different datasets of graphical documents, camera-based warped documents, noisy images containing seals, etc. The results demonstrate that our approach is robust and invariant to size and orientation of the text lines present in the document. |
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ RPL2012b | Serial | 2134 | ||
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| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
| Title | Personalization and User Verification in Wearable Systems using Biometric Walking Patterns | Type | Journal Article | ||
| Year | 2012 | Publication | Personal and Ubiquitous Computing | Abbreviated Journal | PUC |
| Volume |
16 | Issue | 5 | Pages | 563-580 |
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| Abstract | In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| ISSN | 1617-4909 | ISBN | Medium | ||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPR2012 | Serial | 1706 | ||
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| Author | Francesco Ciompi; Oriol Pujol; Carlo Gatta; Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | HoliMab: A Holistic Approach for Media-Adventitia Border Detection in Intravascular Ultrasound | Type | Journal Article | ||
| Year | 2012 | Publication | Medical Image Analysis | Abbreviated Journal | MIA |
| Volume |
16 | Issue | 6 | Pages | 1085-1100 |
| Keywords | Media–Adventitia border detection; Intravascular ultrasound; Multi-Scale Stacked Sequential Learning; Error-correcting output codes; Holistic segmentation | ||||
| Abstract | We present a fully automatic methodology for the detection of the Media-Adventitia border (MAb) in human coronary artery in Intravascular Ultrasound (IVUS) images. A robust border detection is achieved by means of a holistic interpretation of the detection problem where the target object, i.e. the media layer, is considered as part of the whole vessel in the image and all the relationships between tissues are learnt. A fairly general framework exploiting multi-class tissue characterization as well as contextual information on the morphology and the appearance of the tissues is presented. The methodology is (i) validated through an exhaustive comparison with both Inter-observer variability on two challenging databases and (ii) compared with state-of-the-art methods for the detection of the MAb in IVUS. The obtained averaged values for the mean radial distance and the percentage of area difference are 0.211 mm and 10.1%, respectively. The applicability of the proposed methodology to clinical practice is also discussed. | ||||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPG2012 | Serial | 1995 | ||
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| Author | Santiago Segui; Michal Drozdzal; Fernando Vilariño; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria | ||||
| Title | Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy | Type | Journal Article | ||
| Year | 2012 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
| Volume |
16 | Issue | 6 | Pages | 1341-1352 |
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| Abstract | Wireless capsule endoscopy (WCE) is a device that allows the direct visualization of gastrointestinal tract with minimal discomfort for the patient, but at the price of a large amount of time for screening. In order to reduce this time, several works have proposed to automatically remove all the frames showing intestinal content. These methods label frames as {intestinal content – clear} without discriminating between types of content (with different physiological meaning) or the portion of image covered. In addition, since the presence of intestinal content has been identified as an indicator of intestinal motility, its accurate quantification can show a potential clinical relevance. In this paper, we present a method for the robust detection and segmentation of intestinal content in WCE images, together with its further discrimination between turbid liquid and bubbles. Our proposal is based on a twofold system. First, frames presenting intestinal content are detected by a support vector machine classifier using color and textural information. Second, intestinal content frames are segmented into {turbid, bubbles, and clear} regions. We show a detailed validation using a large dataset. Our system outperforms previous methods and, for the first time, discriminates between turbid from bubbles media. | ||||
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| ISSN | 1089-7771 | ISBN | Medium | ||
| Area | 800 | Expedition | Conference | ||
| Notes | MILAB; MV; OR;SIAI | Approved | no | ||
| Call Number | Admin @ si @ SDV2012 | Serial | 2124 | ||
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| Author | Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin-Yuste; Manel Sabate; Petia Radeva | ||||
| Title | Accurate coronary centerline extraction, caliber estimation and catheter detection in angiographies | Type | Journal Article | ||
| Year | 2012 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
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16 | Issue | 6 | Pages | 1332-1340 |
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| Abstract | Segmentation of coronary arteries in X-Ray angiography is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities which allows physicians rapid access to different medical imaging information from Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). In this paper, we propose an accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection. Vesselness, geodesic paths, and a new multi-scale edgeness map are combined to customize the Graph-cuts approach to the segmentation of tubular structures, by means of a global optimization of the Graph-cuts energy function. Moreover, a novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection. We evaluate the method performance on three datasets coming from different imaging systems. The method performs as good as the expert observer w.r.t. centerline detection and caliber estimation. Moreover, the method discriminates between arteries and catheter with an accuracy of 96.5%, sensitivity of 72%, and precision of 97.4%. | ||||
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| ISSN | 1089-7771 | ISBN | Medium | ||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ HGE2012 | Serial | 2141 | ||
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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 |
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| 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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| ISSN | 1057-7149 | ISBN | Medium | ||
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| 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 |
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21 | Issue | 5 | Pages | 2681-2692 |
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| 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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| ISSN | 1057-7149 | ISBN | Medium | ||
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| Notes | ALTRES;ISE | Approved | no | ||
| Call Number | Admin @ si @ SHS2012 | Serial | 1847 | ||
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