{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:17:12Z","timestamp":1773415032130,"version":"3.50.1"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031433597","type":"print"},{"value":"9783031433603","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-43360-3_9","type":"book-chapter","created":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T06:01:53Z","timestamp":1694066513000},"page":"101-113","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Investigation of\u00a0Action Recognition for\u00a0Improving Pedestrian Intent Prediction"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9583-6710","authenticated-orcid":false,"given":"Sarfraz","family":"Ahmed","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6831-846X","authenticated-orcid":false,"given":"Chitta","family":"Saha","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5376-881X","authenticated-orcid":false,"given":"M. Nazmul","family":"Huda","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,8]]},"reference":[{"key":"9_CR1","doi-asserted-by":"crossref","unstructured":"Ahmed, S., Bazi, A.A., Saha, C., Rajbhandari, S., Huda, M.N.: Multi-scale pedestrian intent prediction using 3D joint information as spatio-temporal representation. Expert Syst. Appl. 225, 120077 (2023)","DOI":"10.1016\/j.eswa.2023.120077"},{"key":"9_CR2","doi-asserted-by":"crossref","unstructured":"Cheng, B., Xiao, B., Wang, J., Shi, H., Huang, T.S., Zhang, L.: HigherhrNet: scale-aware representation learning for bottom-up human pose estimation. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 5385\u20135394 (2020)","DOI":"10.1109\/CVPR42600.2020.00543"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Fang, Z., L\u00f3pez, A.M.: Is the pedestrian going to cross? Answering by 2D pose estimation. In: IEEE Intelligent Vehicles Symposium, Proceedings, vol. 2018-June, pp. 1271\u20131276 (2018)","DOI":"10.1109\/IVS.2018.8500413"},{"key":"9_CR4","doi-asserted-by":"crossref","unstructured":"Fang, Z., V\u00e1zquez, D., L\u00f3pez, A., Fang, Z., V\u00e1zquez, D., L\u00f3pez, A.M.: On-board detection of pedestrian intentions. Sensors. 17(10), 2193 (2017)","DOI":"10.3390\/s17102193"},{"issue":"12","key":"9_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/a13120331","volume":"13","author":"J Gesnouin","year":"2020","unstructured":"Gesnouin, J., Pechberti, S., Bresson, G., Stanciulescu, B., Moutarde, F.: Predicting intentions of pedestrians from 2d skeletal pose sequences with a representation-focused multi-branch deep learning network. Algorithms 13(12), 1\u201323 (2020)","journal-title":"Algorithms"},{"key":"9_CR6","doi-asserted-by":"publisher","unstructured":"Kwak, J.Y., Ko, B.C., Nam, J.Y.: Pedestrian intention prediction based on dynamic fuzzy automata for vehicle driving at nighttime. Infrared Phys. Technol. 81, 41\u201351 (3 2017). https:\/\/doi.org\/10.1016\/J.INFRARED.2016.12.014","DOI":"10.1016\/J.INFRARED.2016.12.014"},{"issue":"2","key":"9_CR7","doi-asserted-by":"publisher","first-page":"3485","DOI":"10.1109\/LRA.2020.2976305","volume":"5","author":"B Liu","year":"2020","unstructured":"Liu, B., Adeli, E., Cao, Z., Lee, K.H., Shenoi, A., Gaidon, A., Niebles, J.C.: Spatiotemporal relationship reasoning for pedestrian intent prediction. IEEE Robot. Autom. Lett. 5(2), 3485\u20133492 (2020)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Rasouli, A., Kotseruba, I., Kunic, T., Tsotsos, J.: PIE: a large-scale dataset and models for pedestrian intention estimation and trajectory prediction. In: Proceedings of the IEEE International Conference on Computer Vision 2019-October, pp. 6261\u20136270 (2019)","DOI":"10.1109\/ICCV.2019.00636"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Rasouli, A., Kotseruba, I., Tsotsos, J.K.: Agreeing to cross: how drivers and pedestrians communicate. In: 2017 IEEE Intelligent Vehicles Symposium (IV), pp. 264\u2013269. IEEE (2017)","DOI":"10.1109\/IVS.2017.7995730"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Raza, M., Chen, Z., Rehman, S.U., Wang, P., Bao, P.: Appearance based pedestrians\u2019 head pose and body orientation estimation using deep learning. Neurocomputing. 272, 647\u2013659 (2018)","DOI":"10.1016\/j.neucom.2017.07.029"},{"issue":"June","key":"9_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2021.103259","volume":"130","author":"H Razali","year":"2021","unstructured":"Razali, H., Mordan, T., Alahi, A.: Pedestrian intention prediction: a convolutional bottom-up multi-task approach. Transp. Res. Part C. Emerg. Technol. 130(June), 103259 (2021)","journal-title":"Transp. Res. Part C. Emerg. Technol."},{"key":"9_CR12","doi-asserted-by":"crossref","unstructured":"Ridel, D., Rehder, E., Lauer, M., Stiller, C., Wolf, D.: A literature review on the prediction of pedestrian behavior in urban scenarios. In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. vol. 2018, November, pp. 3105\u20133112. Institute of Electrical and Electronics Engineers Inc. (2018)","DOI":"10.1109\/ITSC.2018.8569415"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Samant, A.P., Warhade, K., Gunale, K.: Pedestrian intent detection using skeleton-based prediction for road safety. In: 2021 2nd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS), vol. 130(September), pp. 238\u2013242 (2021)","DOI":"10.1109\/ACCESS51619.2021.9563293"},{"key":"9_CR14","doi-asserted-by":"publisher","unstructured":"Schmidt, S., F\u00e4rber, B.: Pedestrians at the kerb - Recognising the action intentions of humans. Transp. Res. Part F. Traffic Psychol. Behav. 12(4), 300\u2013310 (2009). https:\/\/doi.org\/10.1016\/J.TRF.2009.02.003","DOI":"10.1016\/J.TRF.2009.02.003"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Yang, B., Zhan, W., Wang, P., Chan, C., Cai, Y., Wang, N.: Crossing or not? Context-based recognition of pedestrian crossing intention in the urban environment. IEEE Trans. Intell. Transp. Syst. 23(6), 5338\u20135349 (2022)","DOI":"10.1109\/TITS.2021.3053031"}],"container-title":["Lecture Notes in Computer Science","Towards Autonomous Robotic Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43360-3_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T14:05:08Z","timestamp":1702476308000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43360-3_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031433597","9783031433603"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43360-3_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"8 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"TAROS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Annual Conference Towards Autonomous Robotic Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambridge","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"taros2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/taros-conference.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"70","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"57% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23, extended abstract, not included in the volume","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}