Transferability of labels between multilens cameras
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913658676707328 |
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| author | Páez-Ubieta, Ignacio de Loyola Frau-Alfaro, Daniel Puente, Santiago T. |
| author_facet | Páez-Ubieta, Ignacio de Loyola Frau-Alfaro, Daniel Puente, Santiago T. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_11513 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Transferability of labels between multilens cameras Páez-Ubieta, Ignacio de Loyola Frau-Alfaro, Daniel Puente, Santiago T. Computer Vision and Pattern Recognition 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. |
| title | Transferability of labels between multilens cameras |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2501.11513 |