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Author |
Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard |
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Title |
A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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Volume |
6388 |
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Pages |
93–98 |
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Abstract |
We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR. |
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Springer, Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-17710-1 |
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ICPR |
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DAG |
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no |
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Call Number |
DAG @ dag @ LLR2010 |
Serial |
1459 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling |
Type |
Book Chapter |
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Year |
2003 |
Publication |
Energy Minimization Methods In Computer Vision And Pattern Recognition |
Abbreviated Journal |
LNCS |
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Volume |
2683 |
Issue |
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Pages |
357-372 |
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Keywords |
Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature |
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Abstract |
Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time. |
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Springer, Berlin |
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Lisbon, PORTUGAL |
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Springer, B. |
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Series Title |
Lecture Notes in Computer Science |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
3-540-40498-8 |
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IAM;MILAB |
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no |
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Call Number |
IAM @ iam @ GIR2003b |
Serial |
1535 |
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Author |
Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados |
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Title |
Textual Descriptions for Browsing People by Visual Apperance. |
Type |
Book Chapter |
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Year |
2002 |
Publication |
Lecture Notes in Artificial Intelligence |
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Volume |
2504 |
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Pages |
419-429 |
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Abstract |
This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building |
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Springer Verlag |
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DAG;CIC |
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no |
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Call Number |
CAT @ cat @ TBB2002b |
Serial |
319 |
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Author |
Fernando Vilariño; Petia Radeva |
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Title |
Patch-Optimized Discriminant Active Contours for Medical Image Segmentation. |
Type |
Conference Article |
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Year |
2002 |
Publication |
Iberoamerican Conference on Artificial Intelligence |
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Address |
Sevilla, Espanya |
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Publisher |
Springer Verlag |
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IBERAMIA |
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Notes |
MV;MILAB;SIAI |
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no |
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Call Number |
BCNPCL @ bcnpcl @ ViR2002; IAM @ iam @ VRa2003 |
Serial |
320 |
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Author |
Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions |
Type |
Book Chapter |
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Year |
2006 |
Publication |
9th International Conference on Medical Image Computing and Computer–Assisted Intervention |
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Volume |
4191 |
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Pages |
161–168 |
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Abstract |
Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions. |
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Address |
Copenhagen (Denmark) |
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Publisher |
Springer Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
R. Larsen, M. Nielsen, and J. Sporring |
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LNCS |
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800 |
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Conference |
MICCAI06 |
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Notes |
MV;OR;MILAB;SIAI |
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no |
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Call Number |
BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006 |
Serial |
725 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva |
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Title |
Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions |
Type |
Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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Volume |
4225 |
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Pages |
178–187 |
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Abstract |
This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns. |
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Address |
Cancun (Mexico) |
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Publisher |
Springer Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
.F. Mart ́ınez-Trinidad et al |
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LNCS |
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800 |
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Notes |
MV;OR;MILAB;SIAI |
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no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f |
Serial |
728 |
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Permanent link to this record |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva |
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Title |
A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment |
Type |
Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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Volume |
4225 |
Issue |
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Pages |
188–197 |
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Abstract |
Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment. |
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Cancun (Mexico) |
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Publisher |
Springer Verlag |
Place of Publication |
Berlin-Heidelberg |
Editor |
J.P. Martinez–Trinidad et al |
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LNCS |
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Area |
800 |
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Conference |
CIARP06 |
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Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e |
Serial |
729 |
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Permanent link to this record |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data |
Type |
Conference Article |
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Year |
2007 |
Publication |
Advances in Computer Graphics and Computer Vision, |
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354–366 |
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Springer Verlag |
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J. Braz, A. Ranchordas, H. Araujo and J. Jorge, |
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VISAPP |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ DoS2007d |
Serial |
1046 |
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Author |
Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez |
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Title |
Automatic Key Pose Selection for 3D Human Action Recognition |
Type |
Conference Article |
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Year |
2010 |
Publication |
6th International Conference on Articulated Motion and Deformable Objects |
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Volume |
6169 |
Issue |
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Pages |
290–299 |
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Abstract |
This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition. |
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Springer Verlag |
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0302-9743 |
ISBN |
978-3-642-14060-0 |
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AMDO |
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Notes |
ISE |
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no |
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Call Number |
DAG @ dag @ GBR2010 |
Serial |
1317 |
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Permanent link to this record |
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Author |
Ernest Valveny; Enric Marti |
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Title |
Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition |
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Journal Article |
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Year |
2000 |
Publication |
Graphics Recognition Recent Advances |
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Volume |
1941 |
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193-208 |
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We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols. |
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Corporate Author |
Springer Verlag |
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Springer Verlag |
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DAG;IAM; |
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no |
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IAM @ iam @ MVA2000 |
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1655 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Learning photometric invariance for object detection |
Type |
Journal Article |
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Year |
2010 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
90 |
Issue |
1 |
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45-61 |
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Keywords |
road detection |
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Abstract |
Impact factor: 3.508 (the last available from JCR2009SCI). Position 4/103 in the category Computer Science, Artificial Intelligence. Quartile
Color is a powerful visual cue in many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions that negatively affect the performance of the task at hand. Often, a reflection model (e.g., Lambertian or dichromatic reflectance) is used to derive color invariant models. However, this approach may be too restricted to model real-world scenes in which different reflectance mechanisms can hold simultaneously.
Therefore, in this paper, we aim to derive color invariance by learning from color models to obtain diversified color invariant ensembles. First, a photometrical orthogonal and non-redundant color model set is computed composed of both color variants and invariants. Then, the proposed method combines these color models to arrive at a diversified color ensemble yielding a proper balance between invariance (repeatability) and discriminative power (distinctiveness). To achieve this, our fusion method uses a multi-view approach to minimize the estimation error. In this way, the proposed method is robust to data uncertainty and produces properly diversified color invariant ensembles. Further, the proposed method is extended to deal with temporal data by predicting the evolution of observations over time.
Experiments are conducted on three different image datasets to validate the proposed method. Both the theoretical and experimental results show that the method is robust against severe variations in imaging conditions. The method is not restricted to a certain reflection model or parameter tuning, and outperforms state-of-the-art detection techniques in the field of object, skin and road recognition. Considering sequential data, the proposed method (extended to deal with future observations) outperforms the other methods |
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Springer US |
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0920-5691 |
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ADAS;ISE |
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no |
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ADAS @ adas @ AGL2010c |
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1451 |
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Author |
Palaiahnakote Shivakumara; Anjan Dutta; Chew Lim Tan; Umapada Pal |
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Title |
Multi-oriented scene text detection in video based on wavelet and angle projection boundary growing |
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Journal Article |
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Year |
2014 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
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72 |
Issue |
1 |
Pages |
515-539 |
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In this paper, we address two complex issues: 1) Text frame classification and 2) Multi-oriented text detection in video text frame. We first divide a video frame into 16 blocks and propose a combination of wavelet and median-moments with k-means clustering at the block level to identify probable text blocks. For each probable text block, the method applies the same combination of feature with k-means clustering over a sliding window running through the blocks to identify potential text candidates. We introduce a new idea of symmetry on text candidates in each block based on the observation that pixel distribution in text exhibits a symmetric pattern. The method integrates all blocks containing text candidates in the frame and then all text candidates are mapped on to a Sobel edge map of the original frame to obtain text representatives. To tackle the multi-orientation problem, we present a new method called Angle Projection Boundary Growing (APBG) which is an iterative algorithm and works based on a nearest neighbor concept. APBG is then applied on the text representatives to fix the bounding box for multi-oriented text lines in the video frame. Directional information is used to eliminate false positives. Experimental results on a variety of datasets such as non-horizontal, horizontal, publicly available data (Hua’s data) and ICDAR-03 competition data (camera images) show that the proposed method outperforms existing methods proposed for video and the state of the art methods for scene text as well. |
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Springer US |
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1380-7501 |
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Notes |
DAG; 600.077 |
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no |
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Call Number |
Admin @ si @ SDT2014 |
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2357 |
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Permanent link to this record |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
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Title |
Coloring Action Recognition in Still Images |
Type |
Journal Article |
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Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
105 |
Issue |
3 |
Pages |
205-221 |
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Abstract |
In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification. |
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Springer US |
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0920-5691 |
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CIC; ADAS; 600.057; 600.048 |
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Admin @ si @ KRW2013 |
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2285 |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
A Novel Space Variant Image Representation |
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Journal Article |
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Year |
2013 |
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Journal of Mathematical Imaging and Vision |
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JMIV |
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47 |
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1-2 |
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48-59 |
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Space-variant representation; Log-polar mapping; Onboard vision applications |
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Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. |
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Springer US |
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0924-9907 |
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ADAS; 600.055; 605.203; 601.215 |
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Admin @ si @ OnS2013a |
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2243 |
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Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Title |
Rendering ground truth data sets to detect shadows cast by static objects in outdoors |
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2014 |
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Multimedia Tools and Applications |
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MTAP |
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70 |
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1 |
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557-571 |
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Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection |
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In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically. |
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Springer US |
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1380-7501 |
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OR;MV |
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Admin @ si @ ISR2014 |
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2229 |
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