{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T16:02:57Z","timestamp":1783180977991,"version":"3.54.6"},"reference-count":16,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T00:00:00Z","timestamp":1675728000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A dynamic vision sensor is an optical sensor that focuses on dynamic changes and outputs event information containing only position, time, and polarity. It has the advantages of high temporal resolution, high dynamic range, low data volume, and low power consumption. However, a single event can only indicate that the increase or decrease in light exceeds the threshold at a certain pixel position and a certain moment. In order to further study the ability and characteristics of event information to represent targets, this paper proposes an event information visualization method with adaptive temporal resolution. Compared with methods with constant time intervals and a constant number of events, it can better convert event information into pseudo-frame images. Additionally, in order to explore whether the pseudo-frame image can efficiently complete the task of target detection according to its characteristics, this paper designs a target detection network named YOLOE. Compared with other algorithms, it has a more balanced detection effect. By constructing a dataset and conducting experimental verification, the detection accuracy of the image obtained by the event information visualization method with adaptive temporal resolution was 5.11% and 4.74% higher than that obtained using methods with a constant time interval and number of events, respectively. The average detection accuracy of pseudo-frame images in the YOLOE network designed in this paper is 85.11%, and the number of detection frames per second is 109. Therefore, the effectiveness of the proposed visualization method and the good performance of the designed detection network are verified.<\/jats:p>","DOI":"10.3390\/s23041839","type":"journal-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T02:04:16Z","timestamp":1675821856000},"page":"1839","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Visualization and Object Detection Based on Event Information"],"prefix":"10.3390","volume":"23","author":[{"given":"Yinghong","family":"Fang","sequence":"first","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongjie","family":"Piao","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoguang","family":"Xie","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Li","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Li","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haolin","family":"Ji","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Xu","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0820-6161","authenticated-orcid":false,"given":"Tan","family":"Gao","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Lichtsteiner, P., Posch, C., and Delbruck, T. (2006, January 6\u20139). A 128 x 128 120db 30mw asynchronous vision sensor that responds to relative intensity change. Proceedings of the 2006 IEEE International Solid State Circuits Conference-Digest of Technical Papers, San Francisco, CA, USA.","DOI":"10.1109\/ISSCC.2006.1696265"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1109\/JSSC.2007.914337","article-title":"A 128x 128 120 dB 15\u03bc s Latency Asynchronous Temporal Contrast Vision Sensor","volume":"43","author":"Patrick","year":"2008","journal-title":"IEEE J. Solid-State Circuits"},{"key":"ref_3","first-page":"71002A","article-title":"A temporal contrast IR vision sensor. Optical Design and Engineering III","volume":"7100","author":"Posch","year":"2008","journal-title":"Int. Soc. Opt. Photonics"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"15117","DOI":"10.1109\/JSEN.2020.3009687","article-title":"Event-Based Object Detection and Tracking for Space Situational Awareness","volume":"20","author":"Afshar","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1007\/s40295-018-00140-5","article-title":"Event-based Sensing for Space Situational Awareness","volume":"66","author":"Cohen","year":"2019","journal-title":"J. Astronaut. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1109\/JPROC.2014.2346153","article-title":"Retinomorphic event-based vision sensors: Bioinspired cameras with spiking output","volume":"102","author":"Posch","year":"2014","journal-title":"Proc. IEEE"},{"key":"ref_7","first-page":"447","article-title":"A review of bioinspired vision sensors and their applications","volume":"27","author":"Cho","year":"2015","journal-title":"Sens. Mater."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1664","DOI":"10.37188\/CJLCD.2021-0149","article-title":"Development status and trend of event-based vision sensor","volume":"36","author":"Fang","year":"2021","journal-title":"Chin. J. Liq. Cryst. Disp."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1109\/JSSC.2010.2085952","article-title":"A QVGA 143 dB dynamic range frame-free PWM image sensor with lossless pixel-level video compression and time-domain CDS","volume":"46","author":"Posch","year":"2010","journal-title":"IEEE J. Solid-State Circuits"},{"key":"ref_10","unstructured":"Bemer, R., Brandli, C., Yang, M., Liu, S.C., and Delbruck, T. (2013, January 12\u201314). A 240\u00d7 180 10 mW 12 us latency sparse-output vision sensor for mobile applications. Proceedings of the 2013 Symposium on VLSI Circuits, Kyoto, Japan."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1109\/JSSC.2014.2342715","article-title":"A 240\u00d7 180 130 db 3 \u00b5s latency global shutter spatiotemporal vision sensor","volume":"49","author":"Brandli","year":"2014","journal-title":"IEEE J. Solid-State Circuits"},{"key":"ref_12","unstructured":"Boettiger, J.P. (2021). A comparative Evaluation of the Detection and Tracking Capability between Novel Event-Based and Conventional Frame-Based Sensors. [Master\u2019s Thesis, Air Force Institute of Technology]."},{"key":"ref_13","unstructured":"Feng, Y. (2021). Research on Event Stream Processing Method of Dynamic Vision Sensor. [Ph.D. Thesis, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Science, University of Chinese Academy of Sciences]."},{"key":"ref_14","unstructured":"Zhang, Y.X. (2019). Research on Feature Extraction and Classification of DVS Events Flow. [Master\u2019s Thesis, Xidian University]."},{"key":"ref_15","unstructured":"Qiu, Z.Y. (2020). Research on Object Detection and Recognition Algorithm Based on Dynamic Vision Sensor. [Master\u2019s Thesis, Harbin Institute of Technology]."},{"key":"ref_16","unstructured":"(2022, September 17). 3 YOLO Introductory Tutorial: YOLOv1 (3) - Improve YOLOv1. Available online: https:\/\/zhuanlan.zhihu.com\/p\/364912692."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/1839\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:26:36Z","timestamp":1760120796000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/1839"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,7]]},"references-count":16,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["s23041839"],"URL":"https:\/\/doi.org\/10.3390\/s23041839","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,7]]}}}