| |
Records |
Links |
|
Author |
David Masip; Michael S. North ; Alexander Todorov; Daniel N. Osherson |
|
| |
Title |
Automated Prediction of Preferences Using Facial Expressions |
Type |
Journal Article |
| |
Year |
2014 |
Publication |
PloS one |
Abbreviated Journal |
Plos |
|
| |
Volume |
9 |
Issue |
2 |
Pages |
e87434 |
|
| |
Keywords |
|
|
| |
Abstract  |
We introduce a computer vision problem from social cognition, namely, the automated detection of attitudes from a person's spontaneous facial expressions. To illustrate the challenges, we introduce two simple algorithms designed to predict observers’ preferences between images (e.g., of celebrities) based on covert videos of the observers’ faces. The two algorithms are almost as accurate as human judges performing the same task but nonetheless far from perfect. Our approach is to locate facial landmarks, then predict preference on the basis of their temporal dynamics. The database contains 768 videos involving four different kinds of preferences. We make it publically available. |
|
| |
Address |
|
|
| |
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 |
|
|
| |
Notes |
OR;MV |
Approved |
no |
|
| |
Call Number |
Admin @ si @ MNT2014 |
Serial |
2453 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño |
|
| |
Title |
WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Computerized Medical Imaging and Graphics |
Abbreviated Journal |
CMIG |
|
| |
Volume |
43 |
Issue |
|
Pages |
99-111 |
|
| |
Keywords |
Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection |
|
| |
Abstract |
We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice. |
|
| |
Address |
|
|
| |
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 |
0895-6111 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
MV; IAM; 600.047; 600.060; 600.075;SIAI |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BSF2015 |
Serial |
2609 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Victor Ponce; Sergio Escalera; Marc Perez; Oriol Janes; Xavier Baro |
|
| |
Title |
Non-Verbal Communication Analysis in Victim-Offender Mediations |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
|
| |
Volume |
67 |
Issue |
1 |
Pages |
19-27 |
|
| |
Keywords |
Victim–Offender Mediation; Multi-modal human behavior analysis; Face and gesture recognition; Social signal processing; Computer vision; Machine learning |
|
| |
Abstract |
We present a non-invasive ambient intelligence framework for the semi-automatic analysis of non-verbal communication applied to the restorative justice field. We propose the use of computer vision and social signal processing technologies in real scenarios of Victim–Offender Mediations, applying feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues from the fields of psychology and observational methodology. We test our methodology on data captured in real Victim–Offender Mediation sessions in Catalonia. We define the ground truth based on expert opinions when annotating the observed social responses. Using different state of the art binary classification approaches, our system achieves recognition accuracies of 86% when predicting satisfaction, and 79% when predicting both agreement and receptivity. Applying a regression strategy, we obtain a mean deviation for the predictions between 0.5 and 0.7 in the range [1–5] for the computed social signals. |
|
| |
Address |
|
|
| |
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 |
|
|
| |
Notes |
HuPBA;MV |
Approved |
no |
|
| |
Call Number |
Admin @ si @ PEP2015 |
Serial |
2583 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
|
| |
Keywords |
|
|
| |
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. |
|
| |
Address |
|
|
| |
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 |
1089-7771 |
ISBN |
|
Medium |
|
|
| |
Area |
800 |
Expedition |
|
Conference |
|
|
| |
Notes |
MILAB; MV; OR;SIAI |
Approved |
no |
|
| |
Call Number |
Admin @ si @ SDV2012 |
Serial |
2124 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
|
| |
Title |
Motility bar: a new tool for motility analysis of endoluminal videos |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Computers in Biology and Medicine |
Abbreviated Journal |
CBM |
|
| |
Volume |
65 |
Issue |
|
Pages |
320-330 |
|
| |
Keywords |
Small intestine; Motility; WCE; Computer vision; Image classification |
|
| |
Abstract |
Wireless Capsule Endoscopy (WCE) provides a new perspective of the small intestine, since it enables, for the first time, visualization of the entire organ. However, the long visual video analysis time, due to the large number of data in a single WCE study, was an important factor impeding the widespread use of the capsule as a tool for intestinal abnormalities detection. Therefore, the introduction of WCE triggered a new field for the application of computational methods, and in particular, of computer vision. In this paper, we follow the computational approach and come up with a new perspective on the small intestine motility problem. Our approach consists of three steps: first, we review a tool for the visualization of the motility information contained in WCE video; second, we propose algorithms for the characterization of two motility building-blocks: contraction detector and lumen size estimation; finally, we introduce an approach to detect segments of stable motility behavior. Our claims are supported by an evaluation performed with 10 WCE videos, suggesting that our methods ably capture the intestinal motility information. |
|
| |
Address |
|
|
| |
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 |
|
|
| |
Notes |
MILAB;MV |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DSR2015 |
Serial |
2635 |
|
| Permanent link to this record |
