|
Records |
Links |
|
Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
|
|
Title |
Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy |
Type |
Conference Article |
|
Year |
2011 |
Publication |
In MICCAI 2011 Workshop on Computational and Clinical Applications in Abdominal Imaging |
Abbreviated Journal |
|
|
|
Volume |
6668 |
Issue |
|
Pages |
76-83 |
|
|
Keywords |
|
|
|
Abstract |
This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed method consists of defining, for each point, a series of radial sectors around it and then accumulates the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming other approaches that also integrate depth of valleys information. |
|
|
Address |
Toronto, Canada |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Link |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
ABI |
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
IAM @ iam @ BSV2011d |
Serial |
1698 |
|
Permanent link to this record |
|
|
|
|
Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
|
|
Title |
Depth of Valleys Accumulation Algorithm for Object Detection |
Type |
Conference Article |
|
Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
Abbreviated Journal |
|
|
|
Volume |
1 |
Issue |
1 |
Pages |
71-80 |
|
|
Keywords |
Object Recognition, Object Region Identification, Image Analysis, Image Processing |
|
|
Abstract |
This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas. |
|
|
Address |
Lleida |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-60750-841-0 |
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
CCIA |
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
IAM @ iam @ BSV2011b |
Serial |
1699 |
|
Permanent link to this record |
|
|
|
|
Author |
Gerard Lacey; Fernando Vilariño |
|
|
Title |
Endoscopy system with motion sensors |
Type |
Patent |
|
Year |
2011 |
Publication |
US 2011/0032347 A1 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
An endoscopy system (1) comprises an endoscope (2) with a camera (3) at its tip. The endoscope extends through an endoscope guide (4) for guiding movement of the endoscope and for measurement of its movement as it enters the body. The guide (4) comprises a generally conical body (5) having a through passage (105) through which the endoscope (2) extends. A motion sensor comprises an optical transmitter (7) and a detector (8) mounted alongside the passage (105) to measure the insertion-withdrawal linear motion and also rotation of the endoscope by the endoscopist's hand. The system (1) also comprises a flexure controller (10) having wheels operated by the endoscopist. The camera (3), the motion sensor (7/8), and the flexure controller (10) are all connected to a processor (11) which feeds a display. |
|
|
Address |
Jacobson Holman PPLC; 400 Seventh Street, N.W. Suite 600; Whashington DC 20004 DC |
|
|
Corporate Author |
USPTO |
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
|
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
IAM @ iam @ LaV2011 |
Serial |
1703 |
|
Permanent link to this record |
|
|
|
|
Author |
Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln |
|
|
Title |
Identifying Potentially Cancerous Tissues in Chromoendoscopy Images |
Type |
Conference Article |
|
Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
6669 |
Issue |
|
Pages |
709-716 |
|
|
Keywords |
Endoscopy, Computer Assisted Diagnosis, Gradient. |
|
|
Abstract |
The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered. |
|
|
Address |
Las Palmas de Gran Canaria. Spain |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
J. Vitria, J.M. Sanches, and M. Hernandez |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-642-21256-7 |
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
Admin @ si @ RVD2011; IAM @ iam @ RVD2011 |
Serial |
1726 |
|
Permanent link to this record |
|
|
|
|
Author |
Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez |
|
|
Title |
Pattern Recognition and Image Analysis |
Type |
Book Whole |
|
Year |
2011 |
Publication |
5th Iberian Conference Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
6669 |
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Las Palmas de Gran Canaria. Spain |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer-Verlag |
Place of Publication |
Berlin |
Editor |
J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-642-2125 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ VSR2011 |
Serial |
1730 |
|
Permanent link to this record |
|
|
|
|
Author |
Mario Rojas; David Masip; Jordi Vitria |
|
|
Title |
Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models |
Type |
Conference Article |
|
Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
6669 |
Issue |
|
Pages |
371-378 |
|
|
Keywords |
|
|
|
Abstract |
Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. |
|
|
Address |
Las Palmas de Gran Canaria. Spain |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ RMV2011a |
Serial |
1731 |
|
Permanent link to this record |
|
|
|
|
Author |
Fadi Dornaika; Bogdan Raducanu |
|
|
Title |
Subtle Facial Expression Recognition in Still Images and Videos |
Type |
Book Chapter |
|
Year |
2011 |
Publication |
Advances in Face Image Analysis: Techniques and Technologies |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
14 |
Pages |
259-277 |
|
|
Keywords |
|
|
|
Abstract |
This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IGI-Global |
Place of Publication |
New York, USA |
Editor |
Yu-Jin Zhang |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-6152-0991-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ DoR2011 |
Serial |
1751 |
|
Permanent link to this record |
|
|
|
|
Author |
Mario Rojas; David Masip; Jordi Vitria |
|
|
Title |
Predicting Dominance Judgements Automatically: A Machine Learning Approach. |
Type |
Conference Article |
|
Year |
2011 |
Publication |
IEEE International Workshop on Social Behavior Analysis |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
939-944 |
|
|
Keywords |
|
|
|
Abstract |
The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task. |
|
|
Address |
Santa Barbara, CA |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-4244-9140-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
SBA |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ RMV2011b |
Serial |
1760 |
|
Permanent link to this record |
|
|
|
|
Author |
Bogdan Raducanu; Fadi Dornaika |
|
|
Title |
A Discriminative Non-Linear Manifold Learning Technique for Face Recognition |
Type |
Book Chapter |
|
Year |
2011 |
Publication |
Informatics Engineering and Information Science |
Abbreviated Journal |
|
|
|
Volume |
254 |
Issue |
6 |
Pages |
339-353 |
|
|
Keywords |
|
|
|
Abstract |
In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1865-0929 |
ISBN |
978-3-642-25482-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIEIS |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ RaD2011 |
Serial |
1804 |
|
Permanent link to this record |
|
|
|
|
Author |
Mario Rojas; David Masip; A. Todorov; Jordi Vitria |
|
|
Title |
Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models |
Type |
Journal Article |
|
Year |
2011 |
Publication |
PloS one |
Abbreviated Journal |
Plos |
|
|
Volume |
6 |
Issue |
8 |
Pages |
e23323 |
|
|
Keywords |
|
|
|
Abstract |
JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Public Library of Science |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ RMT2011 |
Serial |
1883 |
|
Permanent link to this record |
|
|
|
|
Author |
Ruth Aylett; Ginevra Castellano; Bogdan Raducanu; Ana Paiva; Marc Hanheide |
|
|
Title |
Long-term socially perceptive and interactive robot companions: challenges and future perspectives |
Type |
Conference Article |
|
Year |
2011 |
Publication |
13th International Conference on Multimodal Interaction |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
323-326 |
|
|
Keywords |
human-robot interaction, multimodal interaction, social robotics |
|
|
Abstract |
This paper gives a brief overview of the challenges for multi-model perception and generation applied to robot companions located in human social environments. It reviews the current position in both perception and generation and the immediate technical challenges and goes on to consider the extra issues raised by embodiment and social context. Finally, it briefly discusses the impact of systems that must function continually over months rather than just for a few hours. |
|
|
Address |
Alicante |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
ACM |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-4503-0641-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICMI |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ ACR2011 |
Serial |
1888 |
|
Permanent link to this record |
|
|
|
|
Author |
Arnau Ramisa; Alex Goldhoorn; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras |
|
|
Title |
Combining Invariant Features and the ALV Homing Method for Autonomous Robot Navigation Based on Panoramas |
Type |
Journal Article |
|
Year |
2011 |
Publication |
Journal of Intelligent and Robotic Systems |
Abbreviated Journal |
JIRC |
|
|
Volume |
64 |
Issue |
3-4 |
Pages |
625-649 |
|
|
Keywords |
|
|
|
Abstract |
Biologically inspired homing methods, such as the Average Landmark Vector, are an interesting solution for local navigation due to its simplicity. However, usually they require a modification of the environment by placing artificial landmarks in order to work reliably. In this paper we combine the Average Landmark Vector with invariant feature points automatically detected in panoramic images to overcome this limitation. The proposed approach has been evaluated first in simulation and, as promising results are found, also in two data sets of panoramas from real world environments. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Netherlands |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0921-0296 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
RV;ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ RGA2011 |
Serial |
1728 |
|
Permanent link to this record |
|
|
|
|
Author |
Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras |
|
|
Title |
The IIIA30 MObile Robot Object Recognition Datset |
Type |
Conference Article |
|
Year |
2011 |
Publication |
11th Portuguese Robotics Open |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones. |
|
|
Address |
Lisboa |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
Robotica |
|
|
Notes |
RV;ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ RAV2011 |
Serial |
1777 |
|
Permanent link to this record |