Abstract
For real-time user interaction such as telepresence, we propose an image processing approach for presenting natural images to users in the situation of brightness change. We use a high dynamic range camera for training the contrast enhancement method based on CNN. The advantage of the pro-posed approach is that a large number of multiple exposure images necessary for CNN training can be collected easily by taking some videos with the HDR camera in various environments. We collected HDR camera dataset for training while moving indoors and outdoors on foot about 10 min. The data are 500 images randomly extracted from the video sequence. We compared some types of training data. Even in our easily generated dataset, the generated images showed good results. This makes it possible to generate an image equivalent to the HDR camera with a low-cost standard camera.
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Iwata, K., Suzuki, R., Qiu, Y., Satoh, Y. (2020). Single Image Contrast Enhancement by Training the HDR Camera Data. In: Kurosu, M. (eds) Human-Computer Interaction. Design and User Experience. HCII 2020. Lecture Notes in Computer Science(), vol 12181. Springer, Cham. https://doi.org/10.1007/978-3-030-49059-1_43
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