ÖWF-OD: A Dataset for Object Detection in Archival Film Content
Pages 92 - 96
Abstract
In this paper we propose ÖWF-OD, a new dataset for object detection in archival film content. The dataset enables the evaluation of object detection methods on image data with very different image qualities. 1,000 selected keyframes from 100 hours of video material have been annotated, 4,480 bounding boxes are labeled. In addition to these annotations, image quality measures were calculated for the keyframes in order to assess the influence of image quality on object detection. We evaluate different versions of the YOLO object detector to provide a baseline of object detection results for this dataset. The annotation data and the code to extract the keyframes are provided at https://github.com/TailoredMediaProject/OEWF_ObjectDetection.
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Published In
September 2023
274 pages
ISBN:9798400709128
DOI:10.1145/3617233
Copyright © 2023 ACM.
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Association for Computing Machinery
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Publication History
Published: 30 December 2023
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- Short-paper
- Research
- Refereed limited
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- Austrian Research Promotion Agency (FFG)
- Horizon 2020 Framework Programme
Conference
CBMI 2023
CBMI 2023: 20th International Conference on Content-based Multimedia Indexing
September 20 - 22, 2023
Orleans, France
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