[Company Logo Image]  (*)

Home Up Feedback Contents Search

Scene Understanding   

HeadWheelchair ClipOn EMG SmartSpeakingKeyboard Virtual Multi Stereopsis Plant Phenotype 3D using Octree Limb-Volume measurement using Infrared Depth Sensor Object_Recognition Scene Understanding Field Phenotyping Background Subtraction Human Motion Calibration of VSNs Image-Based Servoing Robot Navigation Path Planning Inverse Kinematics Target Tracking Target Geolocation ODI Virtual Dermatologist CNN Virtual Machines for Image Processing New Models for Parallel Soft Computing



Towards Semantic labeling of 3D Point Clouds

                                                                             by Akshay Jain


   This report describes the progress done by the author in developing a system to use semantic information for understanding scenes and identifying objects. The first two steps to perform this task are segmentation and feature computation.



   For the segmentation step, the point cloud is segmented into different regions based on a region growing algorithm similar to Euclidean clustering but adding smoothness constraint with the Euclidean distance. Then for feature extraction, two sets of features are calculated to represent each segment. These are 2D features which represent the visual appearance of the segments and 3D features which describe their geometry.

  The algorithm was able to classify objects with a classification rate of 76 % when the objects under consideration were different (table top, chair back rest, monitor). It is observed that in all the cases that the classification using only visual features is better than the using only 3D features. When the number of objects to be classified are increased, the classification rate is dropped. But even for small number of objects, for example, wall and floor, the classification rate is not high. The floor is confused a lot with the wall.





Home ] Up ]

Send mail to webmaster@ee.missouri.edu with questions or comments about this web site.
Last modified: 06/26/16
(*) Logo created by James Wong