18 citations · 45 across the 8 of their papers we have counts for
8 papers
Scaled 360 layouts: Revisiting non-central panoramas
Bruno Berenguel-Baeta, Jesus Bermudez-Cameo, Jose J. Guerrero
From a non-central panorama, 3D lines can be recovered by geometric reasoning. However, their sensitivity to noise and the complex geometric modeling required has led these panoram…
Visual Gyroscope: Combination of Deep Learning Features and Direct Alignment for Panoramic Stabilization
Bruno Berenguel-Baeta, Antoine N. Andre, Guillaume Caron +2
In this article we present a visual gyroscope based on equirectangular panoramas. We propose a new pipeline where we take advantage of combining three different methods to obtain a…
Convolution kernel adaptation to calibrated fisheye
Bruno Berenguel-Baeta, Maria Santos-Villafranca, Jesus Bermudez-Cameo +2
Convolution kernels are the basic structural component of convolutional neural networks (CNNs). In the last years there has been a growing interest in fisheye cameras for many appl…
Non-central panorama indoor dataset
Bruno Berenguel-Baeta, Jesus Bermudez-Cameo, Jose J. Guerrero
Omnidirectional images are one of the main sources of information for learning based scene understanding algorithms. However, annotated datasets of omnidirectional images cannot ke…
OmniSCV: An Omnidirectional Synthetic Image Generator for Computer Vision
Bruno Berenguel-Baeta, Jesus Bermudez-Cameo, Jose J. Guerrero
Omnidirectional and 360° images are becoming widespread in industry and in consumer society, causing omnidirectional computer vision to gain attention. Their wide field of view all…
Atlanta Scaled layouts from non-central panoramas
Bruno Berenguel-Baeta, Jesus Bermudez-Cameo, Jose J. Guerrero
In this work we present a novel approach for 3D layout recovery of indoor environments using a non-central acquisition system. From a non-central panorama, full and scaled 3D lines…
Floor extraction and door detection for visually impaired guidance
Bruno Berenguel-Baeta, Manuel Guerrero-Viu, Alejandro de Nova +3
Finding obstacle-free paths in unknown environments is a big navigation issue for visually impaired people and autonomous robots. Previous works focus on obstacle avoidance, howeve…
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions
Bruno Berenguel-Baeta, Jesus Bermudez-Cameo, Jose J. Guerrero
In this work we present FreDSNet, a deep learning solution which obtains semantic 3D understanding of indoor environments from single panoramas. Omnidirectional images reveal task-…