| |
Records |
Links |
|
Author |
Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen |
|
| |
Title |
Combining Holistic and Part-based Deep Representations for Computational Painting Categorization |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
6th International Conference on Multimedia Retrieval |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Automatic analysis of visual art, such as paintings, is a challenging inter-disciplinary research problem. Conventional approaches only rely on global scene characteristics by encoding holistic information for computational painting categorization.We argue that such approaches are sub-optimal and that discriminative common visual structures provide complementary information for painting classification. We present an approach that encodes both the global scene layout and discriminative latent common structures for computational painting categorization. The region of interests are automatically extracted, without any manual part labeling, by training class-specific deformable part-based models. Both holistic and region-of-interests are then described using multi-scale dense convolutional features. These features are pooled separately using Fisher vector encoding and concatenated afterwards in a single image representation. Experiments are performed on a challenging dataset with 91 different painters and 13 diverse painting styles. Our approach outperforms the standard method, which only employs the global scene characteristics. Furthermore, our method achieves state-of-the-art results outperforming a recent multi-scale deep features based approach [11] by 6.4% and 3.8% respectively on artist and style classification. |
|
| |
Address |
New York; USA; June 2016 |
|
| |
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  |
ICMR |
|
| |
Notes |
LAMP; 600.068; 600.079;ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RKW2016 |
Serial |
2763 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jaume Amores; David Geronimo; Antonio Lopez |
|
| |
Title |
Multiple instance and active learning for weakly-supervised object-class segmentation |
Type |
Conference Article |
| |
Year |
2010 |
Publication |
3rd IEEE International Conference on Machine Vision |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
Multiple Instance Learning; Active Learning; Object-class segmentation. |
|
| |
Abstract |
In object-class segmentation, one of the most tedious tasks is to manually segment many object examples in order to learn a model of the object category. Yet, there has been little research on reducing the degree of manual annotation for
object-class segmentation. In this work we explore alternative strategies which do not require full manual segmentation of the object in the training set. In particular, we study the use of bounding boxes as a coarser and much cheaper form of segmentation and we perform a comparative study of several Multiple-Instance Learning techniques that allow to obtain a model with this type of weak annotation. We show that some of these methods can be competitive, when used with coarse
segmentations, with methods that require full manual segmentation of the objects. Furthermore, we show how to use active learning combined with this weakly supervised strategy.
As we see, this strategy permits to reduce the amount of annotation and optimize the number of examples that require full manual segmentation in the training set. |
|
| |
Address |
Hong-Kong |
|
| |
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 |
ICMV |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ AGL2010b |
Serial |
1429 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Katerine Diaz; Francesc J. Ferri; W. Diaz |
|
| |
Title |
Fast Approximated Discriminative Common Vectors using rank-one SVD updates |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
20th International Conference On Neural Information Processing |
Abbreviated Journal |
|
|
| |
Volume |
8228 |
Issue |
III |
Pages |
368-375 |
|
| |
Keywords |
|
|
| |
Abstract |
An efficient incremental approach to the discriminative common vector (DCV) method for dimensionality reduction and classification is presented. The proposal consists of a rank-one update along with an adaptive restriction on the rank of the null space which leads to an approximate but convenient solution. The algorithm can be implemented very efficiently in terms of matrix operations and space complexity, which enables its use in large-scale dynamic application domains. Deep comparative experimentation using publicly available high dimensional image datasets has been carried out in order to properly assess the proposed algorithm against several recent incremental formulations.
K. Diaz-Chito, F.J. Ferri, W. Diaz |
|
| |
Address |
Daegu; Korea; November 2013 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
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 |
978-3-642-42050-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICONIP |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DFD2013 |
Serial |
2439 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
X. Orriols; Ricardo Toledo; X. Binefa; Petia Radeva; Jordi Vitria; Juan J. Villanueva |
|
| |
Title |
Probabilistic Saliency Approach for Elongated Structure Detection using Deformable Models. |
Type |
Conference Article |
| |
Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
3 |
Issue |
|
Pages |
1006-1009 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona. |
|
| |
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 |
ICPR |
|
| |
Notes |
OR;MILAB;ADAS;MV |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ OTB2000 |
Serial |
224 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
David Lloret; Joan Serrat; Antonio Lopez; A. Soler; Juan J. Villanueva |
|
| |
Title |
Retinal image registration using creases as anatomical landmarks. |
Type |
Conference Article |
| |
Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
3 |
Issue |
|
Pages |
207-2010 |
|
| |
Keywords |
|
|
| |
Abstract |
Retinal images are routinely used in ophthalmology to study the optical nerve head and the retina. To assess objectively the evolution of an illness, images taken at different times must be registered. Most methods so far have been designed specifically for a single image modality, like temporal series or stereo pairs of angiographies, fluorescein angiographies or scanning laser ophthalmoscope (SLO) images, which makes them prone to fail when conditions vary. In contrast, the method we propose has shown to be accurate and reliable on all the former modalities. It has been adapted from the 3D registration of CT and MR image to 2D. Relevant features (also known as landmarks) are extracted by means of a robust creaseness operator, and resulting images are iteratively transformed until a maximum in their correlation is achieved. Our method has succeeded in more than 100 pairs tried so far, in all cases including also the scaling as a parameter to be optimized |
|
| |
Address |
Barcelona. |
|
| |
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 |
ICPR |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ LSL2000 c |
Serial |
233 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Ricardo Toledo; X. Orriols; Petia Radeva; X. Binefa; Jordi Vitria; Cristina Cañero; Juan J. Villanueva |
|
| |
Title |
Eigensnakes for vessel segmentation in angiography. |
Type |
Conference Article |
| |
Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
4 |
Issue |
|
Pages |
340-343 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona. |
|
| |
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 |
ICPR |
|
| |
Notes |
OR;MILAB;ADAS;MV |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ TOR2000 |
Serial |
235 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
A. Pujol; Felipe Lumbreras; Javier Varona; Juan J. Villanueva |
|
| |
Title |
Locating people in indoor scenes for real applications. |
Type |
Conference Article |
| |
Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
4 |
Issue |
|
Pages |
632-635 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona. |
|
| |
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 |
ICPR |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ PLV2000 |
Serial |
237 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Cristina Cañero; Petia Radeva; Ricardo Toledo; Juan J. Villanueva; J. Mauri |
|
| |
Title |
3D Curve Reconstruction by Biplane Snakes. |
Type |
Conference Article |
| |
Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
4 |
Issue |
|
Pages |
563-566 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona. |
|
| |
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 |
ICPR |
|
| |
Notes |
MILAB;ADAS |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ CRT2000 |
Serial |
238 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Joan Serrat; Antonio Lopez; David Lloret |
|
| |
Title |
On ridges and valleys. |
Type |
Conference Article |
| |
Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
4 |
Issue |
|
Pages |
59-66 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona |
|
| |
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 |
ICPR |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SLL2000 d |
Serial |
334 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jaume Amores |
|
| |
Title |
Vocabulary-based Approaches for Multiple-Instance Data: a Comparative Study |
Type |
Conference Article |
| |
Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
4246–4250 |
|
| |
Keywords |
|
|
| |
Abstract |
Multiple Instance Learning (MIL) has become a hot topic and many different algorithms have been proposed in the last years. Despite this fact, there is a lack of comparative studies that shed light into the characteristics of the different methods and their behavior in different scenarios. In this paper we provide such an analysis. We include methods from different families, and pay special attention to vocabulary-based approaches, a new family of methods that has not received much attention in the MIL literature. The empirical comparison includes seven databases from four heterogeneous domains, implementations of eight popular MIL methods, and a study of the behavior under synthetic conditions. Based on this analysis, we show that, with an appropriate implementation, vocabulary-based approaches outperform other MIL methods in most of the cases, showing in general a more consistent performance. |
|
| |
Address |
Istanbul, Turkey |
|
| |
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 |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ Amo2010 |
Serial |
1295 |
|
| Permanent link to this record |
