The rapid advances of transportation infrastructure have led to a dramatic increase in the demand for smart systems capable of monitoring traffic and street safety. Fundamental to these applications are a community-based evaluation platform and benchmark for object detection and multi-object tracking. To this end, we organize the AVSS2017 Challenge on Advanced Traffic Monitoring, in conjunction with the International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S), to evaluate the state-of-the-art object detection and multi-object tracking algorithms in the relevance of traffic surveillance. Submitted algorithms are evaluated using the large-scale UA-DETRAC benchmark and evaluation protocol. The benchmark, the evaluation toolkit and the algorithm performance are publicly available from the website http://detrac-db.rit.albany.edu.

UA-DETRAC 2017: report of AVSS2017 & IWT4S challenge on advanced traffic monitoring / Lyu, S; Chang, M-C; Du, D; Wen, L; Qi, H; Li, Y; Wei, Y; Ke, L; Hu, T; Del Coco, M; Carcagni, P; Anisimov, D; Bochinski, E; Galasso, F; Bunyak, F; Han, G; Ye, H; Wang, H; Palaniappan, K; Ozcan, K; Wang, L; Wang, L; Lauer, M; Watcharapinchai, N; Song, N. - (2017). (Intervento presentato al convegno 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017 tenutosi a Lecce; Italy) [10.1109/AVSS.2017.8078560].

UA-DETRAC 2017: report of AVSS2017 & IWT4S challenge on advanced traffic monitoring

Galasso F;
2017

Abstract

The rapid advances of transportation infrastructure have led to a dramatic increase in the demand for smart systems capable of monitoring traffic and street safety. Fundamental to these applications are a community-based evaluation platform and benchmark for object detection and multi-object tracking. To this end, we organize the AVSS2017 Challenge on Advanced Traffic Monitoring, in conjunction with the International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S), to evaluate the state-of-the-art object detection and multi-object tracking algorithms in the relevance of traffic surveillance. Submitted algorithms are evaluated using the large-scale UA-DETRAC benchmark and evaluation protocol. The benchmark, the evaluation toolkit and the algorithm performance are publicly available from the website http://detrac-db.rit.albany.edu.
2017
14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
computer vision; machine learning; detection; recognition
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
UA-DETRAC 2017: report of AVSS2017 & IWT4S challenge on advanced traffic monitoring / Lyu, S; Chang, M-C; Du, D; Wen, L; Qi, H; Li, Y; Wei, Y; Ke, L; Hu, T; Del Coco, M; Carcagni, P; Anisimov, D; Bochinski, E; Galasso, F; Bunyak, F; Han, G; Ye, H; Wang, H; Palaniappan, K; Ozcan, K; Wang, L; Wang, L; Lauer, M; Watcharapinchai, N; Song, N. - (2017). (Intervento presentato al convegno 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017 tenutosi a Lecce; Italy) [10.1109/AVSS.2017.8078560].
File allegati a questo prodotto
File Dimensione Formato  
Lyu_UA-DETRAC_2017.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 265.39 kB
Formato Adobe PDF
265.39 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1317829
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 67
  • ???jsp.display-item.citation.isi??? ND
social impact