Multi-Modal Image Segmentation for Obstacle Detection and Masking

Paper #:
  • 2014-01-0164

Published:
  • 2014-04-01
Citation:
Lee, C., Zhang, H., Nguyen, H., Wu, Y. et al., "Multi-Modal Image Segmentation for Obstacle Detection and Masking," SAE Technical Paper 2014-01-0164, 2014, https://doi.org/10.4271/2014-01-0164.
Pages:
6
Abstract:
A novel multi-modal scene segmentation algorithm for obstacle identification and masking is presented in this work. A co-registered data set is generated from monocular camera and light detection and ranging (LIDAR) sensors. This calibrated data enables 3D scene information to be mapped to time-synchronized 2D camera images, where discontinuities in the ranging data indicate the increased likelihood of obstacle edges. Applications include Advanced Driver Assistance Systems (ADAS) which address lane-departure, pedestrian protection and collision avoidance and require both high-quality image segmentation and computational efficiency. Simulated and experimental results that demonstrate system performance are presented.
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