| Autor: |
Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed Mohammed Shamsul Islam |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Advanced Intelligent Systems, Vol 5, Iss 10, Pp n/a-n/a (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2640-4567 |
| DOI: |
10.1002/aisy.202200439 |
| Popis: |
Predicting future frames through image‐to‐image translation and using these synthetically generated frames for high‐speed ground vehicle teleoperation is a new concept to address latency and enhance operational performance. In the immediate previous work, the image quality of the predicted frames was low and a lot of scene detail was lost. To preserve the structural details of objects and improve overall image quality in the predicted frames, several novel ideas are proposed herein. A filter has been designed to remove noise from dense optical flow components resulting from frame rate inconsistencies. The Pix2Pix base network has been modified and a structure‐aware SSIM‐based perpetual loss function has been implemented. A new dataset of 20 000 training input images and 2000 test input images with a 500 ms delay between the target and input frames has been created. Without any additional video transformation steps, the proposed improved model achieved PSNR of 23.1; SSIM of 0.65; and MS‐SSIM of 0.80, a substantial improvement over our previous work. A Fleiss’ kappa score of >0.40 (0.48 for the modified network and 0.46 for the perpetual loss function) proves the reliability of the model. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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