{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T17:49:38Z","timestamp":1776275378786,"version":"3.50.1"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031729485","type":"print"},{"value":"9783031729492","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-72949-2_4","type":"book-chapter","created":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T15:22:17Z","timestamp":1730301737000},"page":"57-73","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Event-Aided Time-to-Collision Estimation for\u00a0Autonomous Driving"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6196-6165","authenticated-orcid":false,"given":"Jinghang","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7739-4879","authenticated-orcid":false,"given":"Bangyan","family":"Liao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6376-8584","authenticated-orcid":false,"given":"Xiuyuan","family":"Lu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9767-6220","authenticated-orcid":false,"given":"Peidong","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5573-2909","authenticated-orcid":false,"given":"Shaojie","family":"Shen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3201-8873","authenticated-orcid":false,"given":"Yi","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,31]]},"reference":[{"issue":"7","key":"4_CR1","doi-asserted-by":"publisher","first-page":"1547","DOI":"10.1109\/TPAMI.2020.2986748","volume":"42","author":"M Almatrafi","year":"2020","unstructured":"Almatrafi, M., Baldwin, R., Aizawa, K., Hirakawa, K.: Distance surface for event-based optical flow. IEEE Trans. Pattern Anal. Mach. Intell. 42(7), 1547\u20131556 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4_CR2","doi-asserted-by":"crossref","unstructured":"Badki, A., Gallo, O., Kautz, J., Sen, P.: Binary ttc: a temporal geofence for autonomous navigation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12946\u201312955 (2021)","DOI":"10.1109\/CVPR46437.2021.01275"},{"issue":"2","key":"4_CR3","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1109\/TNNLS.2013.2273537","volume":"25","author":"R Benosman","year":"2013","unstructured":"Benosman, R., Clercq, C., Lagorce, X., Ieng, S.H., Bartolozzi, C.: Event-based visual flow. IEEE Trans. Neural Netw. Learn. Syst. 25(2), 407\u2013417 (2013)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"9","DOI":"10.3389\/fnins.2014.00009","volume":"8","author":"X Clady","year":"2014","unstructured":"Clady, X., et al.: Asynchronous visual event-based time-to-contact. Front. Neurosci. 8, 9 (2014)","journal-title":"Front. Neurosci."},{"key":"4_CR5","doi-asserted-by":"crossref","unstructured":"Dagan, E., Mano, O., Stein, G.P., Shashua, A.: Forward collision warning with a single camera. In: IEEE Intelligent Vehicles Symposium, 2004, pp. 37\u201342. IEEE (2004)","DOI":"10.1109\/IVS.2004.1336352"},{"issue":"4","key":"4_CR6","doi-asserted-by":"publisher","first-page":"7627","DOI":"10.1109\/LRA.2021.3100153","volume":"6","author":"R Dinaux","year":"2021","unstructured":"Dinaux, R., Wessendorp, N., Dupeyroux, J., De Croon, G.C.: Faith: fast iterative half-plane focus of expansion estimation using event-based optic flow. IEEE Rob. Autom. Lett. 6(4), 7627\u20137634 (2021)","journal-title":"IEEE Rob. Autom. Lett."},{"key":"4_CR7","unstructured":"Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., Koltun, V.: Carla: an open urban driving simulator. In: Conference on Robot Learning, pp. 1\u201316. PMLR (2017)"},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Falanga, D., Kleber, K., Scaramuzza, D.: Dynamic obstacle avoidance for quadrotors with event cameras. Sci. Rob. 5(40), eaaz9712 (2020)","DOI":"10.1126\/scirobotics.aaz9712"},{"issue":"6","key":"4_CR9","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981)","journal-title":"Commun. ACM"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Gallego, G., Rebecq, H., Scaramuzza, D.: A unifying contrast maximization framework for event cameras, with applications to motion, depth, and optical flow estimation. In: IEEE Conference Computer Vision Pattern Recognition (CVPR), pp. 3867\u20133876 (2018)","DOI":"10.1109\/CVPR.2018.00407"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Hidalgo-Carri\u00f3, J., Gallego, G., Scaramuzza, D.: Event-aided direct sparse odometry. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5781\u20135790 (2022)","DOI":"10.1109\/CVPR52688.2022.00569"},{"key":"4_CR12","unstructured":"J\u00e4hne, B., Haussecker, H., Geissler, P.: Handbook of computer vision and applications, vol.\u00a02. Citeseer (1999)"},{"key":"4_CR13","unstructured":"Jocher, G., et\u00a0al.: Ultralytics\/yolov5: v7. 0-yolov5 sota realtime instance segmentation. Zenodo (2022)"},{"issue":"4","key":"4_CR14","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1068\/p050437","volume":"5","author":"DN Lee","year":"1976","unstructured":"Lee, D.N.: A theory of visual control of braking based on information about time-to-collision. Perception 5(4), 437\u2013459 (1976)","journal-title":"Perception"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Lee, D.N.: The optic flow field: the foundation of vision. Phil. Trans. Roy. Soc. Lond. B Biol. Sci. 290(1038), 169\u2013179 (1980)","DOI":"10.1098\/rstb.1980.0089"},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"Lichtsteiner, P., Posch, C., Delbruck, T.: A 128$$\\times $$128 120 dB 30 mW asynchronous vision sensor that responds to relative intensity change. In: IEEE International Solid-State Circuits Conference (ISSCC), pp. 2060\u20132069 (2006)","DOI":"10.1109\/ISSCC.2006.1696265"},{"issue":"3","key":"4_CR17","doi-asserted-by":"publisher","first-page":"4265","DOI":"10.1109\/LRA.2020.2995332","volume":"5","author":"S Lin","year":"2020","unstructured":"Lin, S., Xu, F., Wang, X., Yang, W., Yu, L.: Efficient spatial-temporal normalization of sae representation for event camera. IEEE Rob. Autom. Lett. 5(3), 4265\u20134272 (2020)","journal-title":"IEEE Rob. Autom. Lett."},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Liu, D., Parra, A., Chin, T.J.: Spatiotemporal registration for event-based visual odometry. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4937\u20134946 (2021)","DOI":"10.1109\/CVPR46437.2021.00490"},{"key":"4_CR19","unstructured":"Liu, M., Delbruck, T.: Adaptive time-slice block-matching optical flow algorithm for dynamic vision sensors. In: BMVC (2018)"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Manglik, A., Weng, X., Ohn-Bar, E., Kitanil, K.M.: Forecasting time-to-collision from monocular video: feasibility, dataset, and challenges. In: 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 8081\u20138088. IEEE (2019)","DOI":"10.1109\/IROS40897.2019.8967730"},{"key":"4_CR21","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-031-25056-9_1","volume-title":"European Conference on Computer Vision","author":"S McLeod","year":"2022","unstructured":"McLeod, S., Meoni, G., Izzo, D., Mergy, A., Liu, D., Latif, Y., Reid, I., Chin, T.J.: Globally optimal event-based divergence estimation for ventral landing. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds.) European Conference on Computer Vision, pp. 3\u201320. Springer, Heidelberg (2022). https:\/\/doi.org\/10.1007\/978-3-031-25056-9_1"},{"key":"4_CR22","doi-asserted-by":"crossref","unstructured":"Meyer, F., Bouthemy, P.: Estimation of time-to-collision maps from first order motion models and normal flows. In: 1992 11th IAPR International Conference on Pattern Recognition, vol.\u00a01, pp. 78\u201382. IEEE Computer Society (1992)","DOI":"10.1109\/ICPR.1992.201512"},{"issue":"6","key":"4_CR23","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1109\/70.338534","volume":"10","author":"FG Meyer","year":"1994","unstructured":"Meyer, F.G.: Time-to-collision from first-order models of the motion field. IEEE Trans. Robot. Autom. 10(6), 792\u2013798 (1994)","journal-title":"IEEE Trans. Robot. Autom."},{"key":"4_CR24","doi-asserted-by":"publisher","unstructured":"Negre, A., Braillon, C., Crowley, J.L., Laugier, C.: Real-time time-to-collision from variation of intrinsic scale. In: Experimental Robotics: The 10th International Symposium on Experimental Robotics, pp. 75\u201384. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-77457-0_8","DOI":"10.1007\/978-3-540-77457-0_8"},{"issue":"10","key":"4_CR25","doi-asserted-by":"publisher","first-page":"1102","DOI":"10.1109\/34.42840","volume":"11","author":"RC Nelson","year":"1989","unstructured":"Nelson, R.C., Aloimonos, J.: Obstacle avoidance using flow field divergence. IEEE Trans. Pattern Anal. Mach. Intell. 11(10), 1102\u20131106 (1989)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4_CR26","doi-asserted-by":"crossref","unstructured":"Nunes, U.M., Perrinet, L.U., Ieng, S.H.: Time-to-contact map by joint estimation of up-to-scale inverse depth and global motion using a single event camera. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 23653\u201323663 (2023)","DOI":"10.1109\/ICCV51070.2023.02162"},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Pan, L., Scheerlinck, C., Yu, X., Hartley, R., Liu, M., Dai, Y.: Bringing a blurry frame alive at high frame-rate with an event camera. In: IEEE Conference on Computer Vision Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.00698"},{"key":"4_CR28","doi-asserted-by":"crossref","unstructured":"Poiesi, F., Cavallaro, A.: Detection of fast incoming objects with a moving camera. In: British Machine Vision Conference (BMVC) (2016)","DOI":"10.5244\/C.30.146"},{"key":"4_CR29","doi-asserted-by":"crossref","unstructured":"Rebecq, H., Horstschaefer, T., Scaramuzza, D.: Real-time visual-inertial odometry for event cameras using keyframe-based nonlinear optimization. In: British Machine Vision Conference (BMVC) (2017)","DOI":"10.5244\/C.31.16"},{"key":"4_CR30","doi-asserted-by":"publisher","first-page":"1964","DOI":"10.1109\/TPAMI.2019.2963386","volume":"43","author":"H Rebecq","year":"2019","unstructured":"Rebecq, H., Ranftl, R., Koltun, V., Scaramuzza, D.: High speed and high dynamic range video with an event camera. IEEE Trans. Pattern Anal. Mach. Intell. 43, 1964\u20131980 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4_CR31","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez-G\u00f3mez, J.P., Tapia, R., Garcia, M.D.M.G., Mart\u00ednez-de Dios, J.R., Ollero, A.: Free as a bird: event-based dynamic sense-and-avoid for ornithopter robot flight. IEEE Rob. Autom. Lett. 7(2), 5413\u20135420 (2022)","DOI":"10.1109\/LRA.2022.3153904"},{"key":"4_CR32","doi-asserted-by":"crossref","unstructured":"Sanket, N.J., et al.: EVDodgeNet: deep dynamic obstacle dodging with event cameras. In: IEEE International Conference on Robotics Automation (ICRA) (2020)","DOI":"10.1109\/ICRA40945.2020.9196877"},{"key":"4_CR33","unstructured":"Shaw, D.C., Shaw, J.Z.: Vehicle collision avoidance system (1996). US Patent 5,529,138"},{"key":"4_CR34","doi-asserted-by":"crossref","unstructured":"Shiba, S., Aoki, Y., Gallego, G.: A fast geometric regularizer to mitigate event collapse in the contrast maximization framework. Adv. Intell. Syst. 2200251 (2022)","DOI":"10.1002\/aisy.202200251"},{"issue":"1","key":"4_CR35","doi-asserted-by":"publisher","first-page":"2","DOI":"10.5772\/5715","volume":"4","author":"K Souhila","year":"2007","unstructured":"Souhila, K., Karim, A.: Optical flow based robot obstacle avoidance. Int. J. Adv. Rob. Syst. 4(1), 2 (2007)","journal-title":"Int. J. Adv. Rob. Syst."},{"key":"4_CR36","doi-asserted-by":"crossref","unstructured":"Stabinger, S., Rodriguez-Sanchez, A., Piater, J.: Monocular obstacle avoidance for blind people using probabilistic focus of expansion estimation. In: 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), pp.\u00a01\u20139. IEEE (2016)","DOI":"10.1109\/WACV.2016.7477608"},{"key":"4_CR37","doi-asserted-by":"crossref","unstructured":"Walters, C., Hadfield, S.: Evreflex: dense time-to-impact prediction for event-based obstacle avoidance. In: 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1304\u20131309. IEEE (2021)","DOI":"10.1109\/IROS51168.2021.9636327"},{"key":"4_CR38","unstructured":"Widman, G., Bauson, W.A., Alland, S.W.: Development of collision avoidance systems at delphi automotive systems. In: Proceedings of International Conference on Intelligent Vehicles, pp. 353\u2013358. Citeseer (1998)"},{"key":"4_CR39","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., Paulus, D.: Simple online and realtime tracking with a deep association metric. In: 2017 IEEE International Conference on Image Processing (ICIP), pp. 3645\u20133649. IEEE (2017)","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"4_CR40","doi-asserted-by":"publisher","first-page":"4868","DOI":"10.1109\/TNNLS.2021.3124580","volume":"34","author":"Y Zhou","year":"2021","unstructured":"Zhou, Y., Gallego, G., Lu, X., Liu, S., Shen, S.: Event-based motion segmentation with spatio-temporal graph cuts. IEEE Trans. Neural Netw. Learn. Syst. 34, 4868\u20134880 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"5","key":"4_CR41","doi-asserted-by":"publisher","first-page":"1433","DOI":"10.1109\/TRO.2021.3062252","volume":"37","author":"Y Zhou","year":"2021","unstructured":"Zhou, Y., Gallego, G., Shen, S.: Event-based stereo visual odometry. IEEE Trans. Rob. 37(5), 1433\u20131450 (2021)","journal-title":"IEEE Trans. Rob."},{"issue":"1","key":"4_CR42","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1109\/TRO.2018.2875382","volume":"35","author":"Y Zhou","year":"2018","unstructured":"Zhou, Y., Li, H., Kneip, L.: Canny-vo: visual odometry with rgb-d cameras based on geometric 3-d-2-d edge alignment. IEEE Trans. Rob. 35(1), 184\u2013199 (2018)","journal-title":"IEEE Trans. Rob."},{"key":"4_CR43","doi-asserted-by":"crossref","unstructured":"Zhu, A.Z., Yuan, L., Chaney, K., Daniilidis, K.: EV-FlowNet: self-supervised optical flow estimation for event-based cameras. In: Robotics: Science and Systems (RSS) (2018)","DOI":"10.15607\/RSS.2018.XIV.062"},{"key":"4_CR44","doi-asserted-by":"crossref","unstructured":"Zhu, A.Z., Yuan, L., Chaney, K., Daniilidis, K.: Unsupervised event-based learning of optical flow, depth, and egomotion. In: IEEE Conference on Computer Vision Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.00108"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72949-2_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T15:41:15Z","timestamp":1730302875000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72949-2_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,31]]},"ISBN":["9783031729485","9783031729492"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72949-2_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,31]]},"assertion":[{"value":"31 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}