Vehicle Detection Based on Probability Hypothesis Density Filter
AbstractIn the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI) in complex environments. However, vision techniques often suffer from false positives and limited field of view. In this paper, a LiDAR based vehicle detection approach is proposed by using the Probability Hypothesis Density (PHD) filter. The proposed approach consists of two phases: the hypothesis generation phase to detect potential objects and the hypothesis verification phase to classify objects. The performance of the proposed approach is evaluated in complex scenarios, compared with the state-of-the-art. View Full-Text
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Zhang, F.; Knoll, A. Vehicle Detection Based on Probability Hypothesis Density Filter. Sensors 2016, 16, 510.
Zhang F, Knoll A. Vehicle Detection Based on Probability Hypothesis Density Filter. Sensors. 2016; 16(4):510.Chicago/Turabian Style
Zhang, Feihu; Knoll, Alois. 2016. "Vehicle Detection Based on Probability Hypothesis Density Filter." Sensors 16, no. 4: 510.
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