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Real-time, high-speed video decompression using a frame- and event-based DAVIS sensor


Brandli, Christian; Muller, Lorenz; Delbruck, Tobi (2014). Real-time, high-speed video decompression using a frame- and event-based DAVIS sensor. In: IEEE International Symposium on Circuits and Systems (ISCAS) 2014, Melbourne, Australia, 1 June 2014 - 5 June 2014, 686-689.

Abstract

Dynamic and active pixel vision sensors (DAVISs) are a new type of sensor that combine a frame-based intensity readout with an event-based temporal contrast readout. This paper demonstrates that these sensors inherently perform high-speed, video compression in each pixel by describing the first decompression algorithm for this data. The algorithm performs an online optimization of the event decoding in real time. Example scenes were recorded by the 240×180 pixel sensor at sub-Hz frame rates and successfully decompressed yielding an equivalent frame rate of 2kHz. A quantitative analysis of the compression quality resulted in an average pixel error of 0.5DN intensity resolution for non-saturating stimuli. The system exhibits an adaptive compression ratio which depends on the activity in a scene; for stationary scenes it can go up to 1862. The low data rate and power consumption of the proposed video compression system make it suitable for distributed sensor networks.

Abstract

Dynamic and active pixel vision sensors (DAVISs) are a new type of sensor that combine a frame-based intensity readout with an event-based temporal contrast readout. This paper demonstrates that these sensors inherently perform high-speed, video compression in each pixel by describing the first decompression algorithm for this data. The algorithm performs an online optimization of the event decoding in real time. Example scenes were recorded by the 240×180 pixel sensor at sub-Hz frame rates and successfully decompressed yielding an equivalent frame rate of 2kHz. A quantitative analysis of the compression quality resulted in an average pixel error of 0.5DN intensity resolution for non-saturating stimuli. The system exhibits an adaptive compression ratio which depends on the activity in a scene; for stationary scenes it can go up to 1862. The low data rate and power consumption of the proposed video compression system make it suitable for distributed sensor networks.

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6 citations in Web of Science®
8 citations in Scopus®
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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:5 June 2014
Deposited On:23 Feb 2015 16:18
Last Modified:16 Aug 2017 00:13
Publisher:Proceedings of 2014 IEEE International Symposium on Circuits and Systems
Series Name:Circuits and Systems (ISCAS), 2014 IEEE International Symposium on
Publisher DOI:https://doi.org/10.1109/ISCAS.2014.6865228

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