|
Records |
Links |
|
Author |
Dennis G. Romero; A. Frizera; Angel D. Sappa; Boris X. Vintimilla; T.F. Bastos |
|
|
Title |
A predictive model for human activity recognition by observing actions and context |
Type |
Conference Article |
|
Year |
2015 |
Publication |
ACIVS 2015 (Advanced Concepts for Intelligent Vision Systems), International Conference on, Catania, Italy, 2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
323 - 333 |
|
|
Keywords |
Edge width, Image blu,r Defocus map, Edge model |
|
|
Abstract |
This paper presents a novel model to estimate human activities – a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach. |
|
|
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 |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
43 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
|
|
Title |
Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture |
Type |
Conference Article |
|
Year |
2017 |
Publication |
19th International Conference on Image Analysis and Processing. |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
287-297 |
|
|
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 |
|
Approved |
no |
|
|
Call Number |
gtsi @ user @ |
Serial |
66 |
|
Permanent link to this record |
|
|
|
|
Author |
Miguel Realpe; Boris X. Vintimilla; L. Vlacic |
|
|
Title |
Towards Fault Tolerant Perception for autonomous vehicles: Local Fusion. |
Type |
Conference Article |
|
Year |
2015 |
Publication |
IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), Siem Reap, 2015. |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
253-258 |
|
|
Keywords |
|
|
|
Abstract |
Many robust sensor fusion strategies have been developed in order to reliably detect the surrounding environments of an autonomous vehicle. However, in real situations there is always the possibility that sensors or other components may fail. Thus, internal modules and sensors need to be monitored to ensure their proper function. This paper introduces a general view of a perception architecture designed to detect and classify obstacles in an autonomous vehicle's environment using a fault tolerant framework, whereas elaborates the object detection and local fusion modules proposed in order to achieve the modularity and real-time process required by the system. |
|
|
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 |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
37 |
|
Permanent link to this record |
|
|
|
|
Author |
Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa |
|
|
Title |
Deep learning based camera pose estimation in multi-view environment. |
Type |
Conference Article |
|
Year |
2018 |
Publication |
14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
224-228 |
|
|
Keywords |
|
|
|
Abstract |
This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from scratch on a large data set that takes as input a pair of images from the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose. |
|
|
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 |
|
Approved |
no |
|
|
Call Number |
gtsi @ user @ |
Serial |
93 |
|
Permanent link to this record |