3D Understanding

3D Understanding

Details

3D Understanding extends the ability of computer vision systems to understand an image from the image plane to the 3D world. It has become more prominent with off-the-shelf 3D sensors, which have been recently used to build large-scale RGB-D datasets. 3D Understanding addresses problems related to 3D reconstruction, scene understanding (ex: layout prediction), object detection, pose estimation, and others. Applications include but are not limited to automatic inspection, robot navigation, human-machine interaction, and object modeling.
 

Selected Publications



 


 Robust Manhattan Frame Estimation from a Single RGB-D Image



 

 

 3D Aware Correction and Completion of Depth Maps in Piecewise Planar Scenes​






Publications

  1. Bernard Ghanem, Ali Thabet, Juan Carlos Niebles, and Fabian Caba, “Robust Manhattan Frame Estimation from a Single RGB-D Image”, Conference on Computer Vision and Pattern Recognition (CVPR 2015)
  2. Ali Thabet, Jean Lahoud, Daniel Asmar, Bernard Ghanem, "3D Aware Correction and Completion of Depth Maps in Piecewise Planar Scenes", Asian Conference on Computer Vision (ACCV 2014)
  3. Bernard Ghanem, Jianming Liang, Jinbo Bi, Marcos Salganicoff, and Arun Krishnan, "Reduction of Lymph Tissue False Positives in Pulmonary Embolism Detection", SPIE Medical Imaging Conference  2007
  4. M. Bernardine Dias, Bernard Ghanem, and Anthony Stentz, "Improving Cost Estimation in Market-Based Coordination of a Distributed Sensing Task", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005)
  5. Bernard Ghanem, Ali Fawaz, and Ghassan Karame, "Real-Time Vision-Based Mobile Robot Navigation in Outdoor Environments", 4th annual AUB Student Conference 2005