Vertex-voting-based polygonal object detection
K. Lang (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Jan van Gemert – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Y. Lin – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Asterios Katsifodimos – Graduation committee member (TU Delft - Web Information Systems)
Silvia Pintea – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
Although the pixel-wise labelling approaches have been exploited in depth and achieve good results in segmentation tasks, the grouped pixels are not ideal output for many end-users. In this paper, we propose a vertex-voting-based approach that can directly extract the polygon representations of objects. In order to better solve overlapping scenarios, we also propose a novel method that distinguishes objects by learning a virtual depth axis. When compared with the state-of-the-art method, our experiments demonstrate that this voting-based method is more robust to occlusion and shows a potential research direction.