| Records |
| Author |
Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
| Title |
Towards Ontological Cognitive System |
Type |
Book Chapter |
| Year |
2013 |
Publication |
Topics in Medical Image Processing and Computational Vision |
Abbreviated Journal |
|
| Volume |
8 |
Issue |
|
Pages |
87-99 |
| Keywords |
|
| Abstract |
The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users. |
| 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 |
2212-9391 |
ISBN |
978-94-007-0725-2 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ISE; 605.203; 302.018; 600.049 |
Approved |
no |
| Call Number |
Admin @ si @ FGT2013 |
Serial |
2287 |
| Permanent link to this record |
| |
|
| |
| Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
| Title |
Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces |
Type |
Book Chapter |
| Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
1-26 |
| Keywords |
|
| Abstract |
Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer New York |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
978-1-4614-4456-5 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ LRL2013b |
Serial |
2271 |
| Permanent link to this record |
| |
|
| |
| Author |
Miquel Ferrer; I. Bardaji; Ernest Valveny; Dimosthenis Karatzas; Horst Bunke |
| Title |
Median Graph Computation by Means of Graph Embedding into Vector Spaces |
Type |
Book Chapter |
| Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
45-72 |
| Keywords |
|
| Abstract |
In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer New York |
Place of Publication |
|
Editor |
Yun Fu; Yungian Ma |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
978-1-4614-4456-5 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FBV2013 |
Serial |
2421 |
| Permanent link to this record |
| |
|
| |
| Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
| Title |
Coloring Action Recognition in Still Images |
Type |
Journal Article |
| Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
| Volume |
105 |
Issue |
3 |
Pages |
205-221 |
| Keywords |
|
| 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. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer US |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0920-5691 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CIC; ADAS; 600.057; 600.048 |
Approved |
no |
| Call Number |
Admin @ si @ KRW2013 |
Serial |
2285 |
| Permanent link to this record |
| |
|
| |
| Author |
Naveen Onkarappa; Angel Sappa |
| Title |
A Novel Space Variant Image Representation |
Type |
Journal Article |
| Year |
2013 |
Publication |
Journal of Mathematical Imaging and Vision |
Abbreviated Journal |
JMIV |
| Volume |
47 |
Issue |
1-2 |
Pages |
48-59 |
| Keywords |
Space-variant representation; Log-polar mapping; Onboard vision applications |
| Abstract |
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. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer US |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0924-9907 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS; 600.055; 605.203; 601.215 |
Approved |
no |
| Call Number |
Admin @ si @ OnS2013a |
Serial |
2243 |
| Permanent link to this record |
| |
|
| |
| Author |
Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin |
| Title |
Striola Magica: a functional explanation of otolith organs |
Type |
Journal Article |
| Year |
2013 |
Publication |
Journal of Computational Neuroscience |
Abbreviated Journal |
JCN |
| Volume |
35 |
Issue |
2 |
Pages |
125-154 |
| Keywords |
Otolith organs ;Striola; Vestibular pathway |
| Abstract |
Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer US |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1573-6873. 2013 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
MILAB |
Approved |
no |
| Call Number |
Admin @ si @DBG2013 |
Serial |
2787 |
| Permanent link to this record |
| |
|
| |
| Author |
Bogdan Raducanu; Fadi Dornaika |
| Title |
Texture-independent recognition of facial expressions in image snapshots and videos |
Type |
Journal Article |
| Year |
2013 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
| Volume |
24 |
Issue |
4 |
Pages |
811-820 |
| Keywords |
|
| Abstract |
This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer-Verlag |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0932-8092 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
OR; 600.046; 605.203;MV |
Approved |
no |
| Call Number |
Admin @ si @ RaD2013 |
Serial |
2230 |
| Permanent link to this record |
