We present a novel framework for robustly understanding the geometrical and semantic structure of a cluttered room from a small number of images captured from different viewpoints. The tasks we seek to address include: i) estimating the 3D layout of the room – that is, the 3D configuration of floor, walls and ceiling; ii) identifying and localizing all the foreground objects in the room. We jointly use multiview geometry constraints and image appearance to identify the best room layout configuration. Extensive experimental evaluation demonstrates that our estimation results are more complete and accurate in estimating 3D room structure and recognizing objects than alternative state-of-the-art algorithms. In addition, we show an augmented reality mobile application to highlight the high accuracy of our method, which may be beneficial to many computer vision applications

Bao, S., Furlan, A., Fei Fei, L., Savarese, S. (2014). Understanding the 3D Layout of a Cluttered Room From Multiple Images. In 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014 (pp.690-697) [10.1109/WACV.2014.6836035].

Understanding the 3D Layout of a Cluttered Room From Multiple Images

FURLAN, AXEL
Primo
;
2014

Abstract

We present a novel framework for robustly understanding the geometrical and semantic structure of a cluttered room from a small number of images captured from different viewpoints. The tasks we seek to address include: i) estimating the 3D layout of the room – that is, the 3D configuration of floor, walls and ceiling; ii) identifying and localizing all the foreground objects in the room. We jointly use multiview geometry constraints and image appearance to identify the best room layout configuration. Extensive experimental evaluation demonstrates that our estimation results are more complete and accurate in estimating 3D room structure and recognizing objects than alternative state-of-the-art algorithms. In addition, we show an augmented reality mobile application to highlight the high accuracy of our method, which may be beneficial to many computer vision applications
Si
paper
Scene understanding, indoor, clutter, moving camera, robotics, computer vision
English
IEEE Winter Conference on Applications of Computer Vision (WACV) March 24-26
978-147994985-4
Bao, S., Furlan, A., Fei Fei, L., Savarese, S. (2014). Understanding the 3D Layout of a Cluttered Room From Multiple Images. In 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014 (pp.690-697) [10.1109/WACV.2014.6836035].
Bao, S; Furlan, A; Fei Fei, L; Savarese, S
File in questo prodotto:
File Dimensione Formato  
wacv2014.pdf

Solo gestori archivio

Dimensione 8.75 MB
Formato Adobe PDF
8.75 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/60184
Citazioni
  • Scopus 28
  • ???jsp.display-item.citation.isi??? 17
Social impact