| |
Records |
Links |
|
Author  |
Oscar Lopes; Miguel Reyes; Sergio Escalera; Jordi Gonzalez |
|
| |
Title |
Spherical Blurred Shape Model for 3-D Object and Pose Recognition: Quantitative Analysis and HCI Applications in Smart Environments |
Type |
Journal Article |
| |
Year |
2014 |
Publication |
IEEE Transactions on Systems, Man and Cybernetics (Part B) |
Abbreviated Journal |
TSMCB |
|
| |
Volume |
44 |
Issue |
12 |
Pages |
2379-2390 |
|
| |
Keywords |
|
|
| |
Abstract |
The use of depth maps is of increasing interest after the advent of cheap multisensor devices based on structured light, such as Kinect. In this context, there is a strong need of powerful 3-D shape descriptors able to generate rich object representations. Although several 3-D descriptors have been already proposed in the literature, the research of discriminative and computationally efficient descriptors is still an open issue. In this paper, we propose a novel point cloud descriptor called spherical blurred shape model (SBSM) that successfully encodes the structure density and local variabilities of an object based on shape voxel distances and a neighborhood propagation strategy. The proposed SBSM is proven to be rotation and scale invariant, robust to noise and occlusions, highly discriminative for multiple categories of complex objects like the human hand, and computationally efficient since the SBSM complexity is linear to the number of object voxels. Experimental evaluation in public depth multiclass object data, 3-D facial expressions data, and a novel hand poses data sets show significant performance improvements in relation to state-of-the-art approaches. Moreover, the effectiveness of the proposal is also proved for object spotting in 3-D scenes and for real-time automatic hand pose recognition in human computer interaction scenarios. |
|
| |
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 |
2168-2267 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
HuPBA; ISE; 600.078;MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @ LRE2014 |
Serial |
2442 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Oriol Pujol; Sergio Escalera; Petia Radeva |
|
| |
Title |
An Incremental Node Embedding Technique for Error Correcting Output Codes |
Type |
Journal |
| |
Year |
2008 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
| |
Volume |
41 |
Issue |
2 |
Pages |
713–725 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
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;HuPBA |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ PER2008 |
Serial |
942 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Oriol Pujol; Petia Radeva; Jordi Vitria |
|
| |
Title |
Discriminant ECOC: A Heuristic Method for Application Dependent Design of Error Correcting Output Codes |
Type |
Journal |
| |
Year |
2006 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(6): 1007–1012 |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
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;MILAB;HuPBA;MV |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ PRV2006a |
Serial |
646 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Oriol Pujol; Petia Radeva |
|
| |
Title |
Texture Segmentation by Statistic Deformable Models |
Type |
Journal |
| |
Year |
2003 |
Publication |
International Journal of Image and Graphics (IJIG) |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
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;HuPBA |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ PuR2003 |
Serial |
432 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Oriol Pujol; Petia Radeva |
|
| |
Title |
Texture Segmentation by Statistical Deformable Models |
Type |
Journal |
| |
Year |
2004 |
Publication |
International Journal of Image and Graphics |
Abbreviated Journal |
IJIG |
|
| |
Volume |
4 |
Issue |
3 |
Pages |
433-452 |
|
| |
Keywords |
Texture segmentation, parametric active contours, statistic snakes |
|
| |
Abstract |
Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model. |
|
| |
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;HuPBA |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ PuR2004a |
Serial |
505 |
|
| Permanent link to this record |
