Complex Object Detection Using Light-Field Plenoptic Camera

Identifying objects with a lot of complex features in an uncontrolled scene is a challenging task in the image processing research field. This article presents the application of robust and invariant feature descriptors together with an optimal, iterative and probabilistic methodology. These methods let to achieve an application of object detection through a homographic transformation matrix. This work is built on the Raytrix R42 Plenoptic camera, for which the camera calibration process is introduced. The results present a homographic transformation that relates spatial information of the reference object in an uncontrolled scene. This approach put forward an efficient performance that overcomes bad lighting and occlusion problems.