2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IP-2.9
Paper Title SEMANTIC SEGMENTATION IN DEPTH DATA : A COMPARATIVE EVALUATION OF IMAGE AND POINT CLOUD BASED METHODS
Authors Jigyasa Singh Katrolia, German Research Centre for Artificial Intelligence, Germany; Lars Kraemer, Technical University of Kaiserslautern, Germany; Jason Rambach, Bruno Mirbach, Didier Stricker, German Research Centre for Artificial Intelligence, Germany
SessionMLR-APPL-IP-2: Machine learning for image processing 2
LocationArea E
Session Time:Monday, 20 September, 15:30 - 17:00
Presentation Time:Monday, 20 September, 15:30 - 17:00
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract The problem of semantic segmentation from depth images can be addressed by segmenting directly in the image domain or at 3D point cloud level. In this paper, we attempt for the first time to provide a study and experimental comparison of the two approaches. Through experiments on three datasets, namely SUN RGB-D, NYUdV2 and our own car in-cabin dataset, we extensively compare various semantic segmentation algorithms, the input to which includes images and point clouds derived from them. Based on this, we offer analysis of the performance and computational cost of these algorithms that can provide guidelines on when each method should be preferred.