1. Group 8: Birane Dia Guorui Li Detection of suspicious objects from 3D features

2. The use of technology in UN peacekeeping operations has been a decisive step with respect to support in UN peacekeeping operations. Now how UN peacekeeping operations could take advantage of laser technology to integrate it in its supporting tools? The combination of laser data and CAD model could be an answer. The registration between laser data and CAD models could have further applications like detection of suspicious objects. INTRODUCTION

3. PROBLEM STATEMENT In many cases, UN peacekeeping are very much concern with security. One of those security concerns is how to discriminate suspicious objects which are supposed to be dangerous (cars, bomb and etc.). How to detect suspicious objects from 3D features is becoming important.

4. METHODOLOGY 1. The registration of the Laser scan dataset and the CAD model. 2. The automatic detection of suspicious objects.

5. METHODOLOGY Register the Laser scan datasets and the CAD model The basic steps (by Bosché, 2010) are:

6. METHODOLOGY Automatic detection of suspicious objects (by Khoshelham, 2007) Acquisition of the normal vectorsStoring vectors by using R-table Reconstruction of the object model from the R-table Cast a vote (an increment) to get the parameters of the object model for all points Bin with maximum vote is the reference point. Points vote for this bin belong to an instance of the object

7. RESULT

8. DISCUSSION As shown, our method can be used to detect suspicious object (change detection). Also we can combine the CAD model and the laser data to judge whether there are suspicious objects in the road. When a disaster happened, we can use this to determine whether the peacekeeping army can go into the city by using the road. Difficulties: Registration may be complex. Method doesn’t include indoor objects or small objects, need further studies.

9. Bosché, F. (2010). Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction. Khoshelham, K. (2007). Extending generalized hough transform to detect 3d objects in laser range data. REFERENCE

10. THANK YOU! QUESTIONS?