The Drone is an unmanned aerial vehicle widely used to take pictures and record videos at high altitude, recording information for applications such as video surveillance, to be able to detect cars and people in real time, the main problem is that both the drone as objects are move, this make difficult the track objects with traditional techniques. Faced this problem, the present research proposes the use of convolutional neural network with multidomain learning (MDNet) and camera movement models for the detection and monitoring of cars based on aerial videos. The propouse obtaining very good results in compare with traditional methods, obtaining a 90 % of success in object tracking, which is useful for practical applications.
|Title of host publication||2020 39th International Conference of the Chilean Computer Science Society, SCCC 2020|
|Publisher||IEEE Computer Society|
|State||Published - 16 Nov 2020|
|Event||39th International Conference of the Chilean Computer Science Society, SCCC 2020 - Coquimbo, Chile|
Duration: 16 Nov 2020 → 20 Nov 2020
|Name||Proceedings - International Conference of the Chilean Computer Science Society, SCCC|
|Conference||39th International Conference of the Chilean Computer Science Society, SCCC 2020|
|Period||16/11/20 → 20/11/20|
Bibliographical notePublisher Copyright:
© 2020 IEEE.
- Multidomain learning
- Object tracking