| |
Records |
Links |
|
Author |
Francisco Javier Orozco; Xavier Roca; Jordi Gonzalez |
|
| |
Title |
Real-Time Gaze Tracking with Appearance-Based Models |
Type |
Journal Article |
| |
Year |
2008 |
Publication |
Machine Vision Applications |
Abbreviated Journal |
MVAP |
|
| |
Volume |
20 |
Issue |
6 |
Pages  |
353-364 |
|
| |
Keywords |
Keywords Eyelid and iris tracking, Appearance models, Blinking, Iris saccade, Real-time gaze tracking |
|
| |
Abstract |
Psychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movement is fast and and hence difficult to use to obtain a precise and robust tracking. Instead, our
method proposed to describe eyelid and iris movements as continuous variables using appearance-based tracking. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques.Thus,
in the proposed method textures are learned on-line from near frontal images and illumination changes, occlusions and fast movements are managed. The method achieves real-time performance by combining two appearance-based trackers to a
backtracking algorithm for eyelid estimation and another for iris estimation. These contributions represent a significant advance towards a reliable gaze motion description for HCI and expression analysis, where the strength of complementary
methodologies are combined to avoid using high quality images, colour information, texture training, camera settings and other time-consuming processes. |
|
| |
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 |
ISE |
Approved |
no |
|
| |
Call Number |
ISE @ ise @ ORG2008 |
Serial |
972 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marco Pedersoli; Jordi Gonzalez; Xu Hu; Xavier Roca |
|
| |
Title |
Toward Real-Time Pedestrian Detection Based on a Deformable Template Model |
Type |
Journal Article |
| |
Year |
2014 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
|
| |
Volume |
15 |
Issue |
1 |
Pages |
355-364 |
|
| |
Keywords |
|
|
| |
Abstract |
Most advanced driving assistance systems already include pedestrian detection systems. Unfortunately, there is still a tradeoff between precision and real time. For a reliable detection, excellent precision-recall such a tradeoff is needed to detect as many pedestrians as possible while, at the same time, avoiding too many false alarms; in addition, a very fast computation is needed for fast reactions to dangerous situations. Recently, novel approaches based on deformable templates have been proposed since these show a reasonable detection performance although they are computationally too expensive for real-time performance. In this paper, we present a system for pedestrian detection based on a hierarchical multiresolution part-based model. The proposed system is able to achieve state-of-the-art detection accuracy due to the local deformations of the parts while exhibiting a speedup of more than one order of magnitude due to a fast coarse-to-fine inference technique. Moreover, our system explicitly infers the level of resolution available so that the detection of small examples is feasible with a very reduced computational cost. We conclude this contribution by presenting how a graphics processing unit-optimized implementation of our proposed system is suitable for real-time pedestrian detection in terms of both accuracy and speed. |
|
| |
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 |
1524-9050 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
ISE; 601.213; 600.078 |
Approved |
no |
|
| |
Call Number |
PGH2014 |
Serial |
2350 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Y. Mori; M.Misawa; Jorge Bernal; M. Bretthauer; S.Kudo; A. Rastogi; Gloria Fernandez Esparrach |
|
| |
Title |
Artificial Intelligence for Disease Diagnosis-the Gold Standard Challenge |
Type |
Journal Article |
| |
Year |
2022 |
Publication |
Gastrointestinal Endoscopy |
Abbreviated Journal |
|
|
| |
Volume |
96 |
Issue |
2 |
Pages |
370-372 |
|
| |
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 |
ISE |
Approved |
no |
|
| |
Call Number |
Admin @ si @ MMB2022 |
Serial |
3701 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez |
|
| |
Title |
Selective Spatio-Temporal Interest Points |
Type |
Journal Article |
| |
Year |
2012 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
|
| |
Volume |
116 |
Issue |
3 |
Pages |
396-410 |
|
| |
Keywords |
|
|
| |
Abstract |
Recent progress in the field of human action recognition points towards the use of Spatio-TemporalInterestPoints (STIPs) for local descriptor-based recognition strategies. In this paper, we present a novel approach for robust and selective STIP detection, by applying surround suppression combined with local and temporal constraints. This new method is significantly different from existing STIP detection techniques and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-video words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on popular benchmark datasets (KTH and Weizmann), more challenging datasets of complex scenes with background clutter and camera motion (CVC and CMU), movie and YouTube video clips (Hollywood 2 and YouTube), and complex scenes with multiple actors (MSR I and Multi-KTH), validates our approach and show state-of-the-art performance. Due to the unavailability of ground truth action annotation data for the Multi-KTH dataset, we introduce an actor specific spatio-temporal clustering of STIPs to address the problem of automatic action annotation of multiple simultaneous actors. Additionally, we perform cross-data action recognition by training on source datasets (KTH and Weizmann) and testing on completely different and more challenging target datasets (CVC, CMU, MSR I and Multi-KTH). This documents the robustness of our proposed approach in the realistic scenario, using separate training and test datasets, which in general has been a shortcoming in the performance evaluation of human action recognition techniques. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Elsevier |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1077-3142 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
ISE |
Approved |
no |
|
| |
Call Number |
Admin @ si @ CHM2012 |
Serial |
1806 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich |
|
| |
Title |
Adaptive Correlation Filters for Pattern Recognition |
Type |
Journal |
| |
Year |
2006 |
Publication |
Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
| |
Volume |
16 |
Issue |
3 |
Pages |
425-431 |
|
| |
Keywords |
Pattern recognition, Correlation filters, A adaptive filters |
|
| |
Abstract |
Adaptive correlation filters based on synthetic discriminant functions (SDFs) for reliable pattern recognition are proposed. A given value of discrimination capability can be achieved by adapting a SDF filter to the input scene. This can be done by iterative training. Computer simulation results obtained with the proposed filters are compared with those of various correlation filters in terms of recognition performance. |
|
| |
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 |
ISE |
Approved |
no |
|
| |
Call Number |
ISE @ ise @ KMA2006a |
Serial |
673 |
|
| Permanent link to this record |
