AUTONOMOUS OBJECT TRACKING WITH DRONES
We propose an extension of a recent work with convolutional neural networks and drones such as Learning to fly by driving (DroNet) that can possibly safely drive a drone autonomously. In other words, we propose a model that will extend this work in order to safely track any object with a drone. The combination of (i) the DroNet architecture and weights to apply to CNNs to avoid the crashes; (ii) combining it with DLIB tracker, a correlation implemented tracker based on Danelljan et al.’s paper ; (iii) the extraction of descriptors using Speeded Up Robust Features; and (iv) Fast ...
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