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\iteman{io-port 05781148}
\itemau{Oliveira, Luciano; Nunes, Urbano; Peixoto, Paulo; Silva, Marco; Moita, Fernando}
\itemti{Semantic fusion of laser and vision in pedestrian detection.}
\itemso{Pattern Recognition 43, No. 10, 3648-3659 (2010).}
\itemab
Summary: 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.
\itemrv{~}
\itemcc{}
\itemut{semantic sensor fusion; pedestrian detection; Markov logic network}
\itemli{doi:10.1016/j.patcog.2010.05.014}
\end