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Countering bias in tracking evaluations
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-6096-3648
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
2018 (engelsk)Inngår i: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications / [ed] Francisco Imai, Alain Tremeau and Jose Braz, Science and Technology Publications, Lda , 2018, Vol. 5, s. 581-587Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Recent years have witnessed a significant leap in visual object tracking performance mainly due to powerfulfeatures, sophisticated learning methods and the introduction of benchmark datasets. Despite this significantimprovement, the evaluation of state-of-the-art object trackers still relies on the classical intersection overunion (IoU) score. In this work, we argue that the object tracking evaluations based on classical IoU score aresub-optimal. As our first contribution, we theoretically prove that the IoU score is biased in the case of largetarget objects and favors over-estimated target prediction sizes. As our second contribution, we propose a newscore that is unbiased with respect to target prediction size. We systematically evaluate our proposed approachon benchmark tracking data with variations in relative target size. Our empirical results clearly suggest thatthe proposed score is unbiased in general.

sted, utgiver, år, opplag, sider
Science and Technology Publications, Lda , 2018. Vol. 5, s. 581-587
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-151306DOI: 10.5220/0006714805810587ISBN: 9789897582905 (tryckt)OAI: oai:DiVA.org:liu-151306DiVA, id: diva2:1248643
Konferanse
13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, January 27-29, Funchal, Madeira
Tilgjengelig fra: 2018-09-17 Laget: 2018-09-17 Sist oppdatert: 2019-06-26bibliografisk kontrollert

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Countering bias in tracking evaluations(2131 kB)21 nedlastinger
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