TY - GEN
T1 - PDAVIS
T2 - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023
AU - Haessig, Germain
AU - Joubert, Damien
AU - Haque, Justin
AU - Milde, Moritz B.
AU - Delbruck, Tobi
AU - Gruev, Viktor
N1 - Fabrication of the polarization filters and travel was partially funded by the Swiss National Science Foundation Sinergia projects #CRSII5-18O316, #CRSII5-18O316 and ONR Global-X N62909-20-1-2078. This material is based upon research supported by, or in part by, the U. S. Office of Naval Research (N62909-20-1-2078, N00014-19-1-2400 and N00014-21-1-2177) and U.S. Air Force Office of Scientific Research (FA9550-18-1-0278). The authors thank G. Cohen, T. Cronin, and A. Kaneev for comments; C. Scheerlinck for help with implementing the CF; S. Blair and A. Pietros for help with aligning and bonding the polarization filter arrays to the DAVIS sensors; S. Blair, Z. Liang, C. Symons, Y. Chen, and Z. Zhu for help with measurements; S. Blair and Z. Zhu for help with data analysis; and L. Iannucci and S. Lake for assistance with the tendon experiments.
PY - 2023
Y1 - 2023
N2 - The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solutions to challenging medical and remote sensing problems. However, these bioinspired frame-based cameras lack the high dynamic range and asynchronous polarization vision capabilities of the stomatopod visual system, limiting temporal resolution to ~12ms and dynamic range to ~72dB. Here we present a novel stomatopod-inspired polarization camera which mimics the sustained and transient biological visual pathways to save power and sample data beyond the maximum Nyquist frame rate. This bio-inspired sensor simultaneously captures both synchronous intensity frames and asynchronous polarization brightness change information with submillisecond latencies over a millionfold range of illumination. Our PDAVIS camera is comprised of 346x260 pixels, organized in 2-by-2 macropixels, which filter the incoming light with four linear polarization filters offset by 45°. Polarization information is reconstructed using both low-cost and low-latency event-based algorithms and more accurate but slower deep neural networks. Our sensor is used to image high dynamic range polarization scenes that vary at high speeds and to observe the dynamical properties of single collagen fibers in a bovine tendon under rapid cyclical loads.Video: https://youtu.be/mFuCeTMWEqY
AB - The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solutions to challenging medical and remote sensing problems. However, these bioinspired frame-based cameras lack the high dynamic range and asynchronous polarization vision capabilities of the stomatopod visual system, limiting temporal resolution to ~12ms and dynamic range to ~72dB. Here we present a novel stomatopod-inspired polarization camera which mimics the sustained and transient biological visual pathways to save power and sample data beyond the maximum Nyquist frame rate. This bio-inspired sensor simultaneously captures both synchronous intensity frames and asynchronous polarization brightness change information with submillisecond latencies over a millionfold range of illumination. Our PDAVIS camera is comprised of 346x260 pixels, organized in 2-by-2 macropixels, which filter the incoming light with four linear polarization filters offset by 45°. Polarization information is reconstructed using both low-cost and low-latency event-based algorithms and more accurate but slower deep neural networks. Our sensor is used to image high dynamic range polarization scenes that vary at high speeds and to observe the dynamical properties of single collagen fibers in a bovine tendon under rapid cyclical loads.Video: https://youtu.be/mFuCeTMWEqY
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U2 - 10.1109/CVPRW59228.2023.00412
DO - 10.1109/CVPRW59228.2023.00412
M3 - Conference contribution
AN - SCOPUS:85170829540
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 3963
EP - 3972
BT - Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023
PB - IEEE Computer Society
Y2 - 18 June 2023 through 22 June 2023
ER -