A New Approach to Moving Object Detection and Segmentation: The XY-shift Frame Differencing

N. Wondimu, N. Wondimu, U. Visser, C. Buche, C. Buche

2023

Abstract

Motion out-weights other low-level saliency features in attracting human attention and defining region of interests. The ability to effectively identify moving objects in a sequence of frames help to solve important computer vision problems, such as moving object detection and segmentation. In this paper, we propose a novel frame differencing technique along with a simple three-stream encoder-decoder architecture to effectively and efficiently detect and segment moving objects in a sequence of frames. Our frame differencing component incorporates a novel self-differencing technique, which we call XY-shift frame differencing, and an improved three-frame differencing technique. We fuse the feature maps from the raw frame and the two outputs of our frame differencing component, and fed them to our transfer-learning based convolutional base, VGG-16. The result from this sub-component is further deconvolved and the desired segmentation map is produced. The effectiveness of our model is evaluated using the re-labeled multi-spectral CDNet-2014 dataset for motion segmentation. The qualitative and quantitative results show that our technique achieves effective and efficient moving object detection and segmentation results relative to the state-of-the-art methods.

Download


Paper Citation


in Bibtex Style

@conference{icaart23,
author={N. Wondimu and U. Visser and C. Buche},
title={A New Approach to Moving Object Detection and Segmentation: The XY-shift Frame Differencing},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={309-318},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011664500003393},
isbn={978-989-758-623-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - A New Approach to Moving Object Detection and Segmentation: The XY-shift Frame Differencing
SN - 978-989-758-623-1
AU - Wondimu N.
AU - Visser U.
AU - Buche C.
PY - 2023
SP - 309
EP - 318
DO - 10.5220/0011664500003393


in Harvard Style

Wondimu N., Visser U. and Buche C. (2023). A New Approach to Moving Object Detection and Segmentation: The XY-shift Frame Differencing. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 309-318. DOI: 10.5220/0011664500003393