K., Kamal (2011) Autonomous target detection using segmented correlation method and tracking via mean shift algorithm. In: 4th International Conference on Mechatronics (ICOM), 17-19 May 2011, Kuala Lumpur, Malaysia.
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Official URL: http://dx.doi.org/10.1109/ICOM.2011.5937148
Abstract
An autonomous, efficient and effective object tracking algorithm was required to autonomously identify and track incoming targets. Then controlling a pan-tilt mounted with the sensing camera to accommodate the target within the camera's field of view and controlling a weapon mounted on the second mechanical pan tilt to lock the target and follow it efficiently and accurately. A hybrid algorithm is derived that is a combination of an intruder identification and localization technique derived from the normalized cross correlation method. Spatial and dimensional parameters of the target are autonomously retrieved from segmented correlation method, which are then used as the input parameters for the mean shift algorithm.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | normalized cross correlation method, autonomous target detection, segmented correlation method, mean shift algorithm, object tracking algorithm, target tracking, pan-tilt mounted camera, sensing camera, weapon, hybrid algorithm |
| Divisions: | Electrical Engineering |
| ID Code: | 45623 |
| Deposited By: | Haliza Zainal |
| Deposited On: | 10 Jun 2015 03:00 |
| Last Modified: | 04 Sep 2017 04:58 |
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