|
Records |
Links |
|
Author |
Estefania Talavera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
R-clustering for egocentric video segmentation |
Type |
Conference Article |
|
Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
Abbreviated Journal |
|
|
|
Volume |
9117 |
Issue |
|
Pages |
327-336 |
|
|
Keywords |
Temporal video segmentation; Egocentric videos; Clustering |
|
|
Abstract |
In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energy-minimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate both techniques in an energy-minimization framework that serves to disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames descriptors. We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. |
|
|
Address |
Santiago de Compostela; España; June 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-19389-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
IbPRIA |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ TDB2015 |
Serial |
2597 |
|
Permanent link to this record |
|
|
|
|
Author |
Onur Ferhat; Arcadi Llanza; Fernando Vilariño |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios |
Type |
Conference Article |
|
Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
Abbreviated Journal |
|
|
|
Volume |
9117 |
Issue |
|
Pages |
569-576 |
|
|
Keywords |
Eye tracking; Gaze estimation; Natural light; Webcam |
|
|
Abstract |
We present an eye tracking system that works with regular webcams. We base our work on open source CVC Eye Tracker [7] and we propose a number of improvements and a novel gaze estimation method. The new method uses features extracted from iris segmentation and it does not fall into the traditional categorization of appearance–based/model–based methods. Our experiments show that our approach reduces the gaze estimation errors by 34 % in the horizontal direction and by 12 % in the vertical direction compared to the baseline system. |
|
|
Address |
Santiago de Compostela; June 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-19389-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
IbPRIA |
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
Admin @ si @ FLV2015a |
Serial |
2646 |
|
Permanent link to this record |
|
|
|
|
Author |
Suman Ghosh; Ernest Valveny |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
A Sliding Window Framework for Word Spotting Based on Word Attributes |
Type |
Conference Article |
|
Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
Abbreviated Journal |
|
|
|
Volume |
9117 |
Issue |
|
Pages |
652-661 |
|
|
Keywords |
Word spotting; Sliding window; Word attributes |
|
|
Abstract |
In this paper we propose a segmentation-free approach to word spotting. Word images are first encoded into feature vectors using Fisher Vector. Then, these feature vectors are used together with pyramidal histogram of characters labels (PHOC) to learn SVM-based attribute models. Documents are represented by these PHOC based word attributes. To efficiently compute the word attributes over a sliding window, we propose to use an integral image representation of the document using a simplified version of the attribute model. Finally we re-rank the top word candidates using the more discriminative full version of the word attributes. We show state-of-the-art results for segmentation-free query-by-example word spotting in single-writer and multi-writer standard datasets. |
|
|
Address |
Santiago de Compostela; June 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-19389-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
IbPRIA |
|
|
Notes |
DAG; 600.077 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GhV2015b |
Serial |
2716 |
|
Permanent link to this record |
|
|
|
|
Author |
Pau Riba; Alicia Fornes; Josep Llados |
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Towards the Alignment of Handwritten Music Scores |
Type |
Conference Article |
|
Year |
2015 |
Publication |
11th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
It is very common to find different versions of the same music work in archives of Opera Theaters. These differences correspond to modifications and annotations from the musicians. From the musicologist point of view, these variations are very interesting and deserve study. This paper explores the alignment of music scores as a tool for automatically detecting the passages that contain such differences. Given the difficulties in the recognition of handwritten music scores, our goal is to align the music scores and at the same time, avoid the recognition of music elements as much as possible. After removing the staff lines, braces and ties, the bar lines are detected. Then, the bar units are described as a whole using the Blurred Shape Model. The bar units alignment is performed by using Dynamic Time Warping. The analysis of the alignment path is used to detect the variations in the music scores. The method has been evaluated on a subset of the CVC-MUSCIMA dataset, showing encouraging results. |
|
|
Address |
Nancy; France; August 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
Bart Lamiroy; Rafael Dueire Lins |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-319-52158-9 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
GREC |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2874 |
|
Permanent link to this record |
|
|
|
|
Author |
Pau Riba; Josep Llados; Alicia Fornes; Anjan Dutta |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Large-scale Graph Indexing using Binary Embeddings of Node Contexts |
Type |
Conference Article |
|
Year |
2015 |
Publication |
10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition |
Abbreviated Journal |
|
|
|
Volume |
9069 |
Issue |
|
Pages |
208-217 |
|
|
Keywords |
Graph matching; Graph indexing; Application in document analysis; Word spotting; Binary embedding |
|
|
Abstract |
Graph-based representations are experiencing a growing usage in visual recognition and retrieval due to their representational power in front of classical appearance-based representations in terms of feature vectors. Retrieving a query graph from a large dataset of graphs has the drawback of the high computational complexity required to compare the query and the target graphs. The most important property for a large-scale retrieval is the search time complexity to be sub-linear in the number of database examples. In this paper we propose a fast indexation formalism for graph retrieval. A binary embedding is defined as hashing keys for graph nodes. Given a database of labeled graphs, graph nodes are complemented with vectors of attributes representing their local context. Hence, each attribute counts the length of a walk of order k originated in a vertex with label l. Each attribute vector is converted to a binary code applying a binary-valued hash function. Therefore, graph retrieval is formulated in terms of finding target graphs in the database whose nodes have a small Hamming distance from the query nodes, easily computed with bitwise logical operators. As an application example, we validate the performance of the proposed methods in a handwritten word spotting scenario in images of historical documents. |
|
|
Address |
Beijing; China; May 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
C.-L.Liu; B.Luo; W.G.Kropatsch; J.Cheng |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-319-18223-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
GbRPR |
|
|
Notes |
DAG; 600.061; 602.006; 600.077 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RLF2015a |
Serial |
2618 |
|
Permanent link to this record |
|
|
|
|
Author |
Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris |
![goto web page url](img/www.gif)
|
|
Title |
Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code |
Type |
Conference Article |
|
Year |
2015 |
Publication |
European Conference on Visual Perception ECVP2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Liverpool; uk; August 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
ECVP |
|
|
Notes |
NEUROBIT; |
Approved |
no |
|
|
Call Number |
Admin @ si @ POW2015 |
Serial |
2633 |
|
Permanent link to this record |
|
|
|
|
Author |
Arash Akbarinia; C. Alejandro Parraga |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Biologically Plausible Colour Naming Model |
Type |
Conference Article |
|
Year |
2015 |
Publication |
European Conference on Visual Perception ECVP2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Poster |
|
|
Address |
Liverpool; UK; August 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
ECVP |
|
|
Notes |
NEUROBIT; 600.068 |
Approved |
no |
|
|
Call Number |
Admin @ si @ AkP2015 |
Serial |
2660 |
|
Permanent link to this record |
|
|
|
|
Author |
Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell |
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Quasi-real time digital assessment of Central Airway Obstruction |
Type |
Conference Article |
|
Year |
2015 |
Publication |
3rd European congress for bronchology and interventional pulmonology ECBIP2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Barcelona; Spain; April 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
ECBIP |
|
|
Notes |
IAM; MV; 600.075 |
Approved |
no |
|
|
Call Number |
SGT2015 |
Serial |
2612 |
|
Permanent link to this record |
|
|
|
|
Author |
Mariella Dimiccoli; Petia Radeva |
![goto web page url](img/www.gif)
|
|
Title |
Lifelogging in the era of outstanding digitization |
Type |
Conference Article |
|
Year |
2015 |
Publication |
International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior. |
|
|
Address |
Verliko Tarmovo; Bulgaria; September 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
DiPP |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @DiR2016 |
Serial |
2792 |
|
Permanent link to this record |
|
|
|
|
Author |
Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Multi-observation Face Recognition in Videos based on Label Propagation |
Type |
Conference Article |
|
Year |
2015 |
Publication |
6th Workshop on Analysis and Modeling of Faces and Gestures AMFG2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
10-17 |
|
|
Keywords |
|
|
|
Abstract |
In order to deal with the huge amount of content generated by social media, especially for indexing and retrieval purposes, the focus shifted from single object recognition to multi-observation object recognition. Of particular interest is the problem of face recognition (used as primary cue for persons’ identity assessment), since it is highly required by popular social media search engines like Facebook and Youtube. Recently, several approaches for graph-based label propagation were proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot cope properly with the rapid and frequent changes in data appearance, a phenomenon intrinsically related with video sequences. In this paper, we
propose a novel approach for efficient and adaptive graph construction, based on a two-phase scheme: (i) the first phase is used to adaptively find the neighbors of a sample and also to find the adequate weights for the minimization function of the second phase; (ii) in the second phase, the
selected neighbors along with their corresponding weights are used to locally and collaboratively estimate the sparse affinity matrix weights. Experimental results performed on Honda Video Database (HVDB) and a subset of video
sequences extracted from the popular TV-series ’Friends’ show a distinct advantage of the proposed method over the existing standard graph construction methods. |
|
|
Address |
Boston; USA; June 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
CVPRW |
|
|
Notes |
LAMP; 600.068; 600.072; |
Approved |
no |
|
|
Call Number |
Admin @ si @ RBD2015 |
Serial |
2627 |
|
Permanent link to this record |
|
|
|
|
Author |
Santiago Segui; Oriol Pujol; Jordi Vitria |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Learning to count with deep object features |
Type |
Conference Article |
|
Year |
2015 |
Publication |
Deep Vision: Deep Learning in Computer Vision, CVPR 2015 Workshop |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
90-96 |
|
|
Keywords |
|
|
|
Abstract |
Learning to count is a learning strategy that has been recently proposed in the literature for dealing with problems where estimating the number of object instances in a scene is the final objective. In this framework, the task of learning to detect and localize individual object instances is seen as a harder task that can be evaded by casting the problem as that of computing a regression value from hand-crafted image features. In this paper we explore the features that are learned when training a counting convolutional neural
network in order to understand their underlying representation.
To this end we define a counting problem for MNIST data and show that the internal representation of the network is able to classify digits in spite of the fact that no direct supervision was provided for them during training.
We also present preliminary results about a deep network that is able to count the number of pedestrians in a scene. |
|
|
Address |
Boston; USA; June 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
CVPRW |
|
|
Notes |
MILAB; HuPBA; OR;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ SPV2015 |
Serial |
2636 |
|
Permanent link to this record |
|
|
|
|
Author |
Xavier Baro; Jordi Gonzalez; Junior Fabian; Miguel Angel Bautista; Marc Oliu; Hugo Jair Escalante; Isabelle Guyon; Sergio Escalera |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
ChaLearn Looking at People 2015 challenges: action spotting and cultural event recognition |
Type |
Conference Article |
|
Year |
2015 |
Publication |
2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1-9 |
|
|
Keywords |
|
|
|
Abstract |
Following previous series on Looking at People (LAP) challenges [6, 5, 4], ChaLearn ran two competitions to be presented at CVPR 2015: action/interaction spotting and cultural event recognition in RGB data. We ran a second round on human activity recognition on RGB data sequences. In terms of cultural event recognition, tens of categories have to be recognized. This involves scene understanding and human analysis. This paper summarizes the two performed challenges and obtained results. Details of the ChaLearn LAP competitions can be found at http://gesture.chalearn.org/. |
|
|
Address |
Boston; EEUU; June 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
CVPRW |
|
|
Notes |
HuPBA;MV |
Approved |
no |
|
|
Call Number |
|
Serial |
2652 |
|
Permanent link to this record |
|
|
|
|
Author |
Andres Traumann; Sergio Escalera; Gholamreza Anbarjafari |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
A New Retexturing Method for Virtual Fitting Room Using Kinect 2 Camera |
Type |
Conference Article |
|
Year |
2015 |
Publication |
2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
75-79 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Boston; EEUU; June 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
CVPRW |
|
|
Notes |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ TEA2015 |
Serial |
2653 |
|
Permanent link to this record |
|
|
|
|
Author |
Ramin Irani; Kamal Nasrollahi; Chris Bahnsen; D.H. Lundtoft; Thomas B. Moeslund; Marc O. Simon; Ciprian Corneanu; Sergio Escalera; Tanja L. Pedersen; Maria-Louise Klitgaard; Laura Petrini |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Spatio-temporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition |
Type |
Conference Article |
|
Year |
2015 |
Publication |
2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
88-95 |
|
|
Keywords |
|
|
|
Abstract |
Pain is a vital sign of human health and its automatic detection can be of crucial importance in many different contexts, including medical scenarios. While most available computer vision techniques are based on RGB, in this paper, we investigate the effect of combining RGB, depth, and thermal
facial images for pain detection and pain intensity level recognition. For this purpose, we extract energies released by facial pixels using a spatiotemporal filter. Experiments on a group of 12 elderly people applying the multimodal approach show that the proposed method successfully detects pain and recognizes between three intensity levels in 82% of the analyzed frames improving more than 6% over RGB only analysis in similar conditions. |
|
|
Address |
Boston; EEUU; June 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
CVPRW |
|
|
Notes |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ INB2015 |
Serial |
2654 |
|
Permanent link to this record |
|
|
|
|
Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera; Albert Clapes; Kamal Nasrollahi; Michael Holte; Thomas B. Moeslund |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Keep it Accurate and Diverse: Enhancing Action Recognition Performance by Ensemble Learning |
Type |
Conference Article |
|
Year |
2015 |
Publication |
IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
22-29 |
|
|
Keywords |
|
|
|
Abstract |
The performance of different action recognition techniques has recently been studied by several computer vision researchers. However, the potential improvement in classification through classifier fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of action learning techniques, each performing the recognition task from a different perspective.
The underlying idea is that instead of aiming a very sophisticated and powerful representation/learning technique, we can learn action categories using a set of relatively simple and diverse classifiers, each trained with different feature set. In addition, combining the outputs of several learners can reduce the risk of an unfortunate selection of a learner on an unseen action recognition scenario.
This leads to having a more robust and general-applicable framework. In order to improve the recognition performance, a powerful combination strategy is utilized based on the Dempster-Shafer theory, which can effectively make use
of diversity of base learners trained on different sources of information. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing enhanced performance of the proposed methodology. |
|
|
Address |
Boston; EEUU; June 2015 |
|
|
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 ![sorted by Conference field, descending order (down)](img/sort_desc.gif) |
CVPRW |
|
|
Notes |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ BGE2015 |
Serial |
2655 |
|
Permanent link to this record |