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PIX2NVS: Parameterized conversion of pixel-domain video frames to neuromorphic vision streams

Bi, Y; Andreopoulos, Y; (2017) PIX2NVS: Parameterized conversion of pixel-domain video frames to neuromorphic vision streams. In: Proceedings of the 2017 IEEE International Conference on Image Processing (ICIP). (pp. pp. 1990-1994). IEEE: Beijing, China. Green open access

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Abstract

We propose and make available a generic pixel-to-neuromorphic vision stream (PIX2NVS) framework in order to allow for the generation of neuromorphic data streams from conventional pixel-domain video frames. In order to quantify the accuracy of our framework against experimentallyderived NVS data from previous work, we also propose and validate two metrics, the Chamfer distance and �-repeatability. The most important application of PIX2NVS will be in the generation of artificial NVS from large annotated video frame collections used in machine learning research, e.g., YouTube8M, YFCC100m, YouTube-BoundingBoxes, thereby transferring these datasets to the neuromorphic domain

Type: Proceedings paper
Title: PIX2NVS: Parameterized conversion of pixel-domain video frames to neuromorphic vision streams
Event: 24th IEEE International Conference on Image Processing (ICIP)
Location: Beijing, PEOPLES R CHINA
Dates: 17 September 2017 - 20 September 2017
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ICIP.2017.8296630
Publisher version: https://doi.org/10.1109/ICIP.2017.8296630
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: dynamic vision sensing, neuromorphic vision, software, video analysis
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10056312
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