Paper Info
Title
Inlida: A 3d Lidar Dataset For People Detection And Tracking In Indoor Environments
Abstract
The objective evaluation of people detectors and trackers is essential to develop high performance and general purpose solutions to these problems. This evaluation can be easily done thanks to the use of annotated datasets, but there are some combinations of sensors and scopes that have not been extensively explored. Namely, the application of large range 3D sensors in indoor environments for people detection purposes has been sparsely studied. To fill this gap, we propose InLiDa, a dataset that consists of six different sequences acquired in two different large indoor environments. The dataset is released with a set of tools valid for its use as benchmark for people detection and tracking proposals. Also baseline results obtained with state-of-the-art techniques for people detection and tracking are presented.
Year
DOI
Venue
2017
10.5220/0006148704840491
PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 6
Keywords
Field
DocType
Indoor Lidar Dataset, People Detection, People Tracking, Benchmark
Computer vision,Computer science,Lidar,Artificial intelligence
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Cristina Romero-González133.52
Álvaro Villena200.34
Daniel González-Medina310.69
Jesus Martinez-gomez4245.76
Luis Rodríguez-Ruiz582.89
Ismael García-varea627536.16