| |
Records |
Links |
|
Author |
Naveen Onkarappa; Angel Sappa |
|
| |
Title |
Synthetic sequences and ground-truth flow field generation for algorithm validation |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
|
| |
Volume  |
74 |
Issue |
9 |
Pages |
3121-3135 |
|
| |
Keywords |
Ground-truth optical flow; Synthetic sequence; Algorithm validation |
|
| |
Abstract |
Research in computer vision is advancing by the availability of good datasets that help to improve algorithms, validate results and obtain comparative analysis. The datasets can be real or synthetic. For some of the computer vision problems such as optical flow it is not possible to obtain ground-truth optical flow with high accuracy in natural outdoor real scenarios directly by any sensor, although it is possible to obtain ground-truth data of real scenarios in a laboratory setup with limited motion. In this difficult situation computer graphics offers a viable option for creating realistic virtual scenarios. In the current work we present a framework to design virtual scenes and generate sequences as well as ground-truth flow fields. Particularly, we generate a dataset containing sequences of driving scenarios. The sequences in the dataset vary in different speeds of the on-board vision system, different road textures, complex motion of vehicle and independent moving vehicles in the scene. This dataset enables analyzing and adaptation of existing optical flow methods, and leads to invention of new approaches particularly for driver assistance systems. |
|
| |
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 |
1380-7501 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
ADAS; 600.055; 601.215; 600.076 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ OnS2014b |
Serial |
2472 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; J. Chazalon; Katerine Diaz |
|
| |
Title |
Augmented Songbook: an Augmented Reality Educational Application for Raising Music Awareness |
Type |
Journal Article |
| |
Year |
2018 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
|
| |
Volume |
77 |
Issue |
11 |
Pages |
13773-13798 |
|
| |
Keywords |
Augmented reality; Document image matching; Educational applications |
|
| |
Abstract |
This paper presents the development of an Augmented Reality mobile application which aims at sensibilizing young children to abstract concepts of music. Such concepts are, for instance, the musical notation or the idea of rhythm. Recent studies in Augmented Reality for education suggest that such technologies have multiple benefits for students, including younger ones. As mobile document image acquisition and processing gains maturity on mobile platforms, we explore how it is possible to build a markerless and real-time application to augment the physical documents with didactic animations and interactive virtual content. Given a standard image processing pipeline, we compare the performance of different local descriptors at two key stages of the process. Results suggest alternatives to the SIFT local descriptors, regarding result quality and computational efficiency, both for document model identification and perspective transform estimation. All experiments are performed on an original and public dataset we introduce here. |
|
| |
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 |
DAG; ADAS; 600.084; 600.121; 600.118; 600.129 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RCD2018 |
Serial |
2996 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira |
|
| |
Title |
Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
|
| |
Volume |
83 |
Issue |
|
Pages |
312-325 |
|
| |
Keywords |
Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives |
|
| |
Abstract |
When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Elsevier B.V. |
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 |
ADAS; 600.086, 600.076 |
Approved |
no |
|
| |
Call Number |
Admin @ si @OSS2016a |
Serial |
2806 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira |
|
| |
Title |
Incremental texture mapping for autonomous driving |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
|
| |
Volume |
84 |
Issue |
|
Pages |
113-128 |
|
| |
Keywords |
Scene reconstruction; Autonomous driving; Texture mapping |
|
| |
Abstract |
Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures. |
|
| |
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 |
ADAS; 600.086 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ OSS2016b |
Serial |
2912 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Sappa; Cristhian A. Aguilera-Carrasco; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo |
|
| |
Title |
Monocular visual odometry: A cross-spectral image fusion based approach |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
|
| |
Volume |
85 |
Issue |
|
Pages |
26-36 |
|
| |
Keywords |
Monocular visual odometry; LWIR-RGB cross-spectral imaging; Image fusion |
|
| |
Abstract |
This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is empirically obtained by means of a mutual information based evaluation metric. The objective is to have a flexible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odometry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Elsevier B.V. |
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 |
ADAS;600.086; 600.076 |
Approved |
no |
|
| |
Call Number |
Admin @ si @SAC2016 |
Serial |
2811 |
|
| Permanent link to this record |
