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David Geronimo; Angel Sappa; Daniel Ponsa; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
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Title |
2D-3D based on-board pedestrian detection system |
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Journal Article |
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2010 |
Publication |
Computer Vision and Image Understanding |
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CVIU |
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114 |
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5 |
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583–595 |
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Pedestrian detection; Advanced Driver Assistance Systems; Horizon line; Haar wavelets; Edge orientation histograms |
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During the next decade, on-board pedestrian detection systems will play a key role in the challenge of increasing traffic safety. The main target of these systems, to detect pedestrians in urban scenarios, implies overcoming difficulties like processing outdoor scenes from a mobile platform and searching for aspect-changing objects in cluttered environments. This makes such systems combine techniques in the state-of-the-art Computer Vision. In this paper we present a three module system based on both 2D and 3D cues. The first module uses 3D information to estimate the road plane parameters and thus select a coherent set of regions of interest (ROIs) to be further analyzed. The second module uses Real AdaBoost and a combined set of Haar wavelets and edge orientation histograms to classify the incoming ROIs as pedestrian or non-pedestrian. The final module loops again with the 3D cue in order to verify the classified ROIs and with the 2D in order to refine the final results. According to the results, the integration of the proposed techniques gives rise to a promising system. |
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Computer Vision and Image Understanding (Special Issue on Intelligent Vision Systems), Vol. 114(5):583-595 |
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1077-3142 |
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ADAS |
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ADAS @ adas @ GSP2010 |
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1341 |
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Debora Gil; Oriol Rodriguez-Leor; Petia Radeva; Josepa Mauri |
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Title |
Myocardial Perfusion Characterization From Contrast Angiography Spectral Distribution |
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Journal Article |
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2008 |
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IEEE Transactions on Medical Imaging |
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27 |
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641-649 |
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Contrast angiography; myocardial perfusion; spectral analysis. |
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Despite recovering a normal coronary flow after acute myocardial infarction, percutaneous coronary intervention does not guarantee a proper perfusion (irrigation) of the infarcted area. This damage in microcirculation integrity may detrimentally affect the patient survival. Visual assessment of the myocardium opacification in contrast angiography serves to define a subjective score of the microcirculation integrity myocardial blush analysis (MBA). Although MBA correlates with patient prognosis its visual assessment is a very difficult task that requires of a highly expertise training in order to achieve a good intraobserver and interobserver agreement. In this paper, we provide objective descriptors of the myocardium staining pattern by analyzing the spectrum of the image local statistics. The descriptors proposed discriminate among the different phenomena observed in the angiographic sequence and allow defining an objective score of the myocardial perfusion. |
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IAM;MILAB |
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IAM @ iam @ GRR2008 |
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1541 |
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Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Personalization and User Verification in Wearable Systems using Biometric Walking Patterns |
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Journal Article |
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2012 |
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Personal and Ubiquitous Computing |
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PUC |
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16 |
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563-580 |
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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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Springer-Verlag |
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1617-4909 |
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MILAB;HuPBA |
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Admin @ si @ CPR2012 |
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1706 |
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Jose Seabra; Francesco Ciompi; Oriol Pujol; Josepa Mauri; Petia Radeva; Joao Sanchez |
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Title |
Rayleigh Mixture Model for Plaque Characterization in Intravascular Ultrasound |
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Journal Article |
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2011 |
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IEEE Transactions on Biomedical Engineering |
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TBME |
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58 |
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1314-1324 |
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Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology. |
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MILAB;HuPBA |
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Admin @ si @ SCP2011 |
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1712 |
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Author |
Eduard Vazquez; Ramon Baldrich; Joost Van de Weijer; Maria Vanrell |
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Title |
Describing Reflectances for Colour Segmentation Robust to Shadows, Highlights and Textures |
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Journal Article |
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2011 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence |
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TPAMI |
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33 |
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917-930 |
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The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost. |
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Los Alamitos; CA; USA; |
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IEEE Computer Society |
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0162-8828 |
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CIC |
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Admin @ si @ VBW2011 |
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1715 |
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Author |
Kaida Xiao; Sophie Wuerger; Chenyang Fu; Dimosthenis Karatzas |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Unique Hue Data for Colour Appearance Models. Part i: Loci of Unique Hues and Hue Uniformity |
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Journal Article |
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2011 |
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Color Research & Application |
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CRA |
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36 |
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316-323 |
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unique hues; colour appearance models; CIECAM02; hue uniformity |
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Psychophysical experiments were conducted to assess unique hues on a CRT display for a large sample of colour-normal observers (n 1⁄4 185). These data were then used to evaluate the most commonly used colour appear- ance model, CIECAM02, by transforming the CIEXYZ tris- timulus values of the unique hues to the CIECAM02 colour appearance attributes, lightness, chroma and hue angle. We report two findings: (1) the hue angles derived from our unique hue data are inconsistent with the commonly used Natural Color System hues that are incorporated in the CIECAM02 model. We argue that our predicted unique hue angles (derived from our large dataset) provide a more reliable standard for colour management applications when the precise specification of these salient colours is im- portant. (2) We test hue uniformity for CIECAM02 in all four unique hues and show significant disagreements for all hues, except for unique red which seems to be invariant under lightness changes. Our dataset is useful to improve the CIECAM02 model as it provides reliable data for benchmarking. |
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Wiley Periodicals Inc |
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DAG |
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Admin @ si @ XWF2011 |
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1816 |
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Author |
Chenyang Fu; Kaida Xiao; Dimosthenis Karatzas; Sophie Wuerger |
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Title |
Investigation of Unique Hue Setting Changes with Ageing |
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Journal Article |
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Year |
2011 |
Publication |
Chinese Optics Letters |
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COL |
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9 |
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053301-1-5 |
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Clromatic sensitivity along the protan, deutan, and tritan lines and the loci of the unique hues (red, green, yellow, blue) for a very large sample (n = 185) of colour-normal observers ranging from 18 to 75 years of age are assessed. Visual judgments are obtained under normal viewing conditions using colour patches on self-luminous display under controlled adaptation conditions. Trivector discrimination thresholds show an increase as a function of age along the protan, deutan, and tritan axes, with the largest increase present along the tritan line, less pronounced shifts in unique hue settings are also observed. Based on the chromatic (protan, deutan, tritan) thresholds and using scaled cone signals, we predict the unique hue changes with ageing. A dependency on age for unique red and unique yellow for predicted hue angle is found. We conclude that the chromatic sensitivity deteriorates significantly with age, whereas the appearance of unique hues is much less affected, remaining almost constant despite the known changes in the ocular media. |
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DAG |
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Admin @ si @ XFW2011 |
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1818 |
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Author |
Sophie Wuerger; Kaida Xiao; Chenyang Fu; Dimosthenis Karatzas |
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Title |
Colour-opponent mechanisms are not affected by age-related chromatic sensitivity changes |
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Journal Article |
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2010 |
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Ophthalmic and Physiological Optics |
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OPO |
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30 |
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635-659 |
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The purpose of this study was to assess whether age-related chromatic sensitivity changes are associated with corresponding changes in hue perception in a large sample of colour-normal observers over a wide age range (n = 185; age range: 18-75 years). In these observers we determined both the sensitivity along the protan, deutan and tritan line; and settings for the four unique hues, from which the characteristics of the higher-order colour mechanisms can be derived. We found a significant decrease in chromatic sensitivity due to ageing, in particular along the tritan line. From the unique hue settings we derived the cone weightings associated with the colour mechanisms that are at equilibrium for the four unique hues. We found that the relative cone weightings (w(L) /w(M) and w(L) /w(S)) associated with the unique hues were independent of age. Our results are consistent with previous findings that the unique hues are rather constant with age while chromatic sensitivity declines. They also provide evidence in favour of the hypothesis that higher-order colour mechanisms are equipped with flexible cone weightings, as opposed to fixed weights. The mechanism underlying this compensation is still poorly understood. |
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DAG; IF: 1.259 |
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Admin @ si @ WXF2010 |
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1826 |
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Author |
J. Stöttinger; A. Hanbury; N. Sebe; Theo Gevers |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Spars Color Interest Points for Image Retrieval and Object Categorization |
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Journal Article |
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2012 |
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IEEE Transactions on Image Processing |
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TIP |
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21 |
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2681-2692 |
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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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1057-7149 |
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ALTRES;ISE |
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Admin @ si @ SHS2012 |
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1847 |
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Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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Title |
Improving Color Constancy by Photometric Edge Weighting |
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2012 |
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IEEE Transaction on Pattern Analysis and Machine Intelligence |
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TPAMI |
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34 |
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918-929 |
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: Edge-based color constancy methods make use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as material, shadow and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant estimation. Therefore, in this paper, an extensive analysis is provided of different edge types on the performance of edge-based color constancy methods. First, an edge-based taxonomy is presented classifying edge types based on their photometric properties (e.g. material, shadow-geometry and highlights). Then, a performance evaluation of edge-based color constancy is provided using these different edge types. From this performance evaluation it is derived that specular and shadow edge types are more valuable than material edges for the estimation of the illuminant. To this end, the (iterative) weighted Grey-Edge algorithm is proposed in which these edge types are more emphasized for the estimation of the illuminant. Images that are recorded under controlled circumstances demonstrate that the proposed iterative weighted Grey-Edge algorithm based on highlights reduces the median angular error with approximately $25\%$. In an uncontrolled environment, improvements in angular error up to $11\%$ are obtained with respect to regular edge-based color constancy. |
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Los Alamitos; CA; USA; |
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0162-8828 |
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CIC;ISE |
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Admin @ si @ GGW2012 |
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1850 |
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Albert Gordo; Alicia Fornes; Ernest Valveny |
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Title |
Writer identification in handwritten musical scores with bags of notes |
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2013 |
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Pattern Recognition |
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PR |
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46 |
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1337-1345 |
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Writer Identification is an important task for the automatic processing of documents. However, the identification of the writer in graphical documents is still challenging. In this work, we adapt the Bag of Visual Words framework to the task of writer identification in handwritten musical scores. A vanilla implementation of this method already performs comparably to the state-of-the-art. Furthermore, we analyze the effect of two improvements of the representation: a Bhattacharyya embedding, which improves the results at virtually no extra cost, and a Fisher Vector representation that very significantly improves the results at the cost of a more complex and costly representation. Experimental evaluation shows results more than 20 points above the state-of-the-art in a new, challenging dataset. |
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0031-3203 |
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Admin @ si @ GFV2013 |
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2307 |
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Michael Holte; Bhaskar Chakraborty; Jordi Gonzalez; Thomas B. Moeslund |
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Title |
A Local 3D Motion Descriptor for Multi-View Human Action Recognition from 4D Spatio-Temporal Interest Points |
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2012 |
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IEEE Journal of Selected Topics in Signal Processing |
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J-STSP |
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6 |
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5 |
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553-565 |
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In this paper, we address the problem of human action recognition in reconstructed 3-D data acquired by multi-camera systems. We contribute to this field by introducing a novel 3-D action recognition approach based on detection of 4-D (3-D space $+$ time) spatio-temporal interest points (STIPs) and local description of 3-D motion features. STIPs are detected in multi-view images and extended to 4-D using 3-D reconstructions of the actors and pixel-to-vertex correspondences of the multi-camera setup. Local 3-D motion descriptors, histogram of optical 3-D flow (HOF3D), are extracted from estimated 3-D optical flow in the neighborhood of each 4-D STIP and made view-invariant. The local HOF3D descriptors are divided using 3-D spatial pyramids to capture and improve the discrimination between arm- and leg-based actions. Based on these pyramids of HOF3D descriptors we build a bag-of-words (BoW) vocabulary of human actions, which is compressed and classified using agglomerative information bottleneck (AIB) and support vector machines (SVMs), respectively. Experiments on the publicly available i3DPost and IXMAS datasets show promising state-of-the-art results and validate the performance and view-invariance of the approach. |
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1932-4553 |
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Santiago Segui; Laura Igual; Jordi Vitria |
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Title |
Bagged One Class Classifiers in the Presence of Outliers |
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2013 |
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International Journal of Pattern Recognition and Artificial Intelligence |
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IJPRAI |
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27 |
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1350014-1350035 |
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One-class Classifier; Ensemble Methods; Bagging and Outliers |
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The problem of training classifiers only with target data arises in many applications where non-target data are too costly, difficult to obtain, or not available at all. Several one-class classification methods have been presented to solve this problem, but most of the methods are highly sensitive to the presence of outliers in the target class. Ensemble methods have therefore been proposed as a powerful way to improve the classification performance of binary/multi-class learning algorithms by introducing diversity into classifiers.
However, their application to one-class classification has been rather limited. In
this paper, we present a new ensemble method based on a non-parametric weighted bagging strategy for one-class classification, to improve accuracy in the presence of outliers. While the standard bagging strategy assumes a uniform data distribution, the method we propose here estimates a probability density based on a forest structure of the data. This assumption allows the estimation of data distribution from the computation of simple univariate and bivariate kernel densities. Experiments using original and noisy versions of 20 different datasets show that bagging ensemble methods applied to different one-class classifiers outperform base one-class classification methods. Moreover, we show that, in noisy versions of the datasets, the non-parametric weighted bagging strategy we propose outperforms the classical bagging strategy in a statistically significant way. |
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OR; 600.046;MV |
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Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco |
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A Neurodynamical Model of Brightness Induction in V1 |
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2013 |
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PloS ONE |
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e64086 |
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Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway. |
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Admin @ si @ POD2013 |
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2242 |
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Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta |
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Title |
On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents |
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Journal Article |
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2012 |
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International Journal of Pattern Recognition and Artificial Intelligence |
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IJPRAI |
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26 |
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1263002-126027 |
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Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025 |
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0,624 JCR
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images. |
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DAG |
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Admin @ si @ LRF2012 |
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2128 |
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