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Fast multiple objects detection and tracking fusing color camera and 3D LIDAR for intelligent vehicles

Soonmin Hwang, Nam Il Kim, Yukyung Choi, Seokju Lee, In So Kweon

Year
2016
Citations
46

Abstract

For many robotics and intelligent vehicle applications, detection and tracking multiple objects (DATMO) is one of the most important components. However, most of the DATMO applications have difficulty in applying real-world applications due to high computational complexity. In this paper, we propose an efficient DATMO framework that fully employs the complementary information from the color camera and the 3D LIDAR. For high efficiency, we present a segmentation scheme by using both 2D and 3D information which gives accurate segments very quickly. In our experiments, we show that our framework can achieve the faster speed (~4Hz) than the state-of-the-art methods reported in KITTI benchmark (>1Hz).

Keywords

Artificial intelligenceBenchmark (surveying)Computer scienceComputer visionLidarSegmentationTracking (education)Object detectionRoboticsImage segmentation

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