Ensembling object detectors for image and video data analysis

• URL: http://arxiv.org/abs/2102.04798v1
• Date: Tue, 9 Feb 2021 12:38:16 GMT
• Title: Ensembling object detectors for image and video data analysis
• Authors: Kateryna Chumachenko, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
• Abstract summary: We propose a method for ensembling the outputs of multiple object detectors for improving detection performance and precision of bounding boxes on image data. We extend it to video data by proposing a two-stage tracking-based scheme for detection refinement.
• Score: 98.26061123111647
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose a method for ensembling the outputs of multiple object detectors for improving detection performance and precision of bounding boxes on image data. We further extend it to video data by proposing a two-stage tracking-based scheme for detection refinement. The proposed method can be used as a standalone approach for improving object detection performance, or as a part of a framework for faster bounding box annotation in unseen datasets, assuming that the objects of interest are those present in some common public datasets.

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