@article{ref1,
title="Semantic fusion of laser and vision in pedestrian detection",
journal="Pattern recognition",
year="2010",
author="Oliveira, Luciano and Nunes, Urbano and Peixoto, Paulo and Silva, Marco and Moita, Fernando",
volume="43",
number="10",
pages="3648-3659",
abstract="Fusion of laser and vision in object detection has been accomplished by two main approaches: (1) independent integration of sensor-driven features or sensor-driven classifiers, or (2) a region of interest (ROI) is found by laser segmentation and an image classifier is used to name the projected ROI. Here, we propose a novel fusion approach based on semantic information, and embodied on many levels. Sensor fusion is based on spatial relationship of parts-based classifiers, being performed via a Markov logic network. The proposed system deals with partial segments, it is able to recover depth information even if the laser fails, and the integration is modeled through contextual information--characteristics not found on previous approaches. Experiments in pedestrian detection demonstrate the effectiveness of our method over data sets gathered in urban scenarios.<p />",
language="",
issn="0031-3203",
doi="10.1016/j.patcog.2010.05.014",
url="http://dx.doi.org/10.1016/j.patcog.2010.05.014"
}