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                    <article article-type="research-article">
                    <front>
                        <journal-meta>
                        <journal-id journal-id-type="publisher-id">ei</journal-id>
                        <journal-title>Electronic Imaging</journal-title>
                        <issn pub-type="ppub">2470-1173</issn><issn pub-type="epub">2470-1173</issn>
                        <publisher>
                            <publisher-name>Society for Imaging Science and Technology</publisher-name>
                            <publisher-loc>IS&amp;T 7003 Kilworth Lane, Springfield, VA 22151 USA</publisher-loc>
                        </publisher>
                        </journal-meta>
                        <article-meta>
                        <article-id pub-id-type="doi">10.2352/EI.2022.34.7.ISS-242</article-id>
                        <article-id pub-id-type="publisher-id">ISS-242</article-id>
                        <article-categories>
                            <subj-group>
                            <subject>Article</subject>
                            </subj-group>
                        </article-categories>
                        <title-group>
                            <article-title>Accurate event simulation using high-speed video</article-title>
                        </title-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Mou</surname>
                                <given-names>Xiaozheng </given-names>
                               </name> <xref ref-type="aff" rid="aff1author1"/></contrib> <aff id="aff1author1">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Feng</surname>
                                <given-names>Kaijun </given-names>
                               </name> <xref ref-type="aff" rid="aff1author2"/></contrib> <aff id="aff1author2">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Yi</surname>
                                <given-names>Alex </given-names>
                               </name> <xref ref-type="aff" rid="aff1author3"/></contrib> <aff id="aff1author3">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Wang</surname>
                                <given-names>Steve </given-names>
                               </name> <xref ref-type="aff" rid="aff1author4"/></contrib> <aff id="aff1author4">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Chen</surname>
                                <given-names>Huan </given-names>
                               </name> <xref ref-type="aff" rid="aff1author5"/></contrib> <aff id="aff1author5">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Hu</surname>
                                <given-names>Xiaoqin </given-names>
                               </name> <xref ref-type="aff" rid="aff1author6"/></contrib> <aff id="aff1author6">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Guo</surname>
                                <given-names>Menghan </given-names>
                               </name> <xref ref-type="aff" rid="aff1author7"/></contrib> <aff id="aff1author7">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Chen</surname>
                                <given-names>Shoushun </given-names>
                               </name> <xref ref-type="aff" rid="aff1author8"/></contrib> <aff id="aff1author8">Omnivision Technologies Inc., United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Suess</surname>
                                <given-names>Andreas </given-names>
                               </name> <xref ref-type="aff" rid="aff1author9"/></contrib> <aff id="aff1author9">Omnivision Technologies Inc., United States</aff></contrib-group><abstract>
                        <title>Abstract</title>
                        <p>Event sensing is a novel modality which is solely sensitive to changes of information. This redundancy reduction can be utilized to achieve high temporal resolution, reduce power consumption, simplify algorithms etc. The hardware-software co-design of event sensors and algorithms requires early simulation of the sensor system. It has been shown that high-speed video is well suited to derive such event data for temporal contrast based event sensors, but the simulators published so far neglect phenomena such as readout latency or refractory period. This paper presents ongoing modeling activities at OmniVision Technologies.</p>
                        </abstract><pub-date>
                            <day>16</day>
                            <month>01</month>
                            <year>2022</year>
                            </pub-date><volume>34</volume>
                        <issue-acronym>ISS</issue-acronym>
                        <issue>7</issue>
                        <fpage>242-1</fpage>
                        <lpage>242-6</lpage>
                        <permissions>
                             <copyright-statement>© 2022, Society for Imaging Science and Technology</copyright-statement>
                            <copyright-year>2022</copyright-year>
                        </permissions><kwd-group><kwd>Event Sensing</kwd><kwd> Neuromorphic Imaging</kwd><kwd> Event simulation</kwd><kwd> Event modeling</kwd><kwd> Latency</kwd></kwd-group></article-meta>
                    </front>
                    </article>