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Semi-Automatic Video Annotation For Object Detection

2021-01-18 10:35:32
Kutalmis Gokalp Ince, Aybora Koksal, Arda Fazla, A. Aydin Alatan

Abstract

In this study, a semi-automatic video annotation method is proposed, utilizing temporal information to eliminate false-positives with a tracking-by-detection approach by employing multiple hypothesis tracking (MHT). MHT method automatically forms tracklets which are confirmed by human operators to enlarge the training set. A novel incremental learning approach helps to annotate videos in an iterative way. The experiments performed on AUTH Multidrone Dataset reveals that the annotation workload can be reduced up to 96% by the proposed approach.

Abstract (translated)

URL

https://arxiv.org/abs/2101.06977

PDF

https://arxiv.org/pdf/2101.06977.pdf


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