Inverted tracking algorithm for the field survey through artificial vision and robotics
The area of artificial vision and robotics has very important advances in the recognition and tracking of objects, not only in indoor scenes but also in outdoor ones. These methods and algorithms have given rise to very important technological advances in different areas of knowledge. In the area of Precision Agriculture, the main problem of its use lies in its application in field surveys, whereas in the case of cultivation, we will have fixed objects (seedlings) in established spaces (furrows and plots), but in uncontrolled environments. The determination of the density of these crops and their distance between furrows among other data is in many cases, relevant to their performance. It is the purpose of this paper to solve the automated sensing of this data through the use of cameras and artificial vision techniques. In this work, an inverted tracking algorithm is defined in order to automatically determine the necessary shot-points by means of which the cameras involved as sensors on a robotic platform capture scene images. This will help to survey the density and distance of the crop to be analyzed.