Transferability of labels between multilens cameras
This incremental work addresses the challenge of labeling objects across multiple camera lenses, potentially expanding the use of multilens cameras beyond satellite or medical imagery to include labeling of invisible objects in the visible spectrum.
The paper tackles the problem of automatically transferring bounding box and mask labels between different lenses on multilens cameras by combining phase correlation with an iterative refinement process, achieving over 90% accuracy in most cases with a processing time of 65 ms.
In this work, a new method for automatically extending Bounding Box (BB) and mask labels across different channels on multilens cameras is presented. For that purpose, the proposed method combines the well known phase correlation method with a refinement process. During the first step, images are aligned by localizing the peak of intensity obtained in the spatial domain after performing the cross correlation process in the frequency domain. The second step consists of obtaining the best possible transformation by using an iterative process maximising the IoU (Intersection over Union) metric. Results show that, by using this method, labels could be transferred across different lens on a camera with an accuracy over 90% in most cases and just by using 65 ms in the whole process. Once the transformations are obtained, artificial RGB images are generated, for labeling them so as to transfer this information into each of the other lens. This work will allow users to use this type of cameras in more fields rather than satellite or medical imagery, giving the chance of labeling even invisible objects in the visible spectrum.