Feature point mapping for agricultural environments using an airborne quadcopter | |
| Author | Shakya, Niraj |
| Call Number | AIT RSPR no.CS-14-01 |
| Subject(s) | Computer vision Vision, Monocular |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Research studies project report ; no. CS-14-01 |
| Abstract | In computer vision the technique when information is obtained from the devices or sensors and then those information is used to make a map or store the information in a map is known as simultaneous localization and mapping (SLAM). This research study presents an analysis of feature point detection and mapping for agricultural environments. I perform feature point map building using the front-facing camera and the bottom-facing camera of an arborne quadcopter. The SLAM technique that I use to detect feature points and build a map is acheived by a single monocular camera. These SLAM techniques gives us the position of the camera trajectory estimates as well as the positions of the feature points estimates it detects. In the future, these techniques could be used for autonomous navigation of an airborne quadcopter in agricultural environments. |
| Year | 2014 |
| Corresponding Series Added Entry | Asian Institute of Technology. Research studies project report ; no. CS-14-01 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Dailey, Matthew; |
| Examination Committee(s) | Mongkol Ekpanyapong;Manukid Parnichkun; |
| Degree | Research report (M. Sc.) - Asian Institute of Technology, 2014 |