The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera
Open accessAbstract
Event-based cameras can measure intensity changes (called ‘events’) with microsecond accuracy under high-speed motion and challenging lighting conditions. With the active pixel sensor (APS), the event camera allows simultaneous output of the intensity frames. However, the output images are captured at a relatively low frame-rate and often suffer from motion blur. A blurry image can be regarded as the integral of a sequence of latent images, while the events indicate the changes between the latent images. Therefore, we are able to model the blur-generation process by associating event data to a latent image. In this paper, we propose a simple and effective approach, the Event-based Double Integral (EDI) model, to reconstruct a high frame-rate, sharp video from a single blurry frame and its event data. The video generation is based on solving a simple non-convex optimization problem in a single scalar variable. Experimental results on both synthetic and real images demonstrate the superiority of our EDI model and optimization method in comparison to the state-of-the-art.
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Cites
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Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring
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A 240 × 180 130 dB 3 µs Latency Global Shutter Spatiotemporal Vision Sensor
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Cited by
Gallego, G., Delbruck, T., Orchard, G., Bartolozzi, C., Taba, B., Censi, A., Leutenegger, S., Davison, A. J., Conradt, J., Daniilidis, K., et al. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3008413 · Cited by 2,566
Metadata
- Authors
- Pan, L., Scheerlinck, C., Yu, X., Hartley, R., Liu, M., & Dai, Y.
- Venue
- 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2019-06
- Pages
- 6813-6822
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2970672284
- Cited by
- 308
- References
- 43
- FWCI
- 8.69
- Type
- conference paper
- Language
- en
- Open access
- green
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- Pan, L., Scheerlinck, C., Yu, X., Hartley, R., Liu, M., & Dai, Y. (2019). Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2019.00698
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