Pedestrian Detection Combining RGB and Dense LIDAR Data
C. Premebida1, J. Carreira1,2, J. Batista1 and U. Nunes1
1ISR, DEEC, Univ. of Coimbra. 2UC Berkeley
  • Dense depth-map upsampling method using only LIDAR
  • 3D Velodyne and camera fusion (experiments: KITTI dataset)
  • Def. Part-Models + SVM-based rescoring strategy
  • High performance on KITTI benchmarking
Results on the KITTI dataset (Fusion-DPM):
Paper: pdf (825KB) IEEE, IROS' 14
\cite: bib

our solution depends on Discriminatively trained deformable part models

R. B. Girshick, P. F. Felzenszwalb, and D. McAllester, “Discriminatively Trained Deformable Part Models, Release 5
LIBSVM is also necessary libsvm-3.12

README, .m and .cpp (mex) files: download