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Panoptic lintention network: Towards efficient navigational perception for the visually impaired

Mao, Wei; Zhang, Jiaming ORCID iD icon; Yang, Kailun; Stiefelhagen, Rainer ORCID iD icon


Classic computer vision algorithms, instance segmentation, and semantic segmentation can not provide a holistic understanding of the surroundings for the visually impaired. In this paper, we utilize panoptic segmentation to assist the navigation of visually impaired people by offering both things and stuff awareness in the proximity of the visually impaired efficiently. To this end, we propose an efficient Attention module -- Lintention which can model long-range interactions in linear time using linear space. Based on Lintention, we then devise a novel panoptic segmentation model which we term Panoptic Lintention Net. Experiments on the COCO dataset indicate that the Panoptic Lintention Net raises the Panoptic Quality (PQ) from 39.39 to 41.42 with 4.6\% performance gain while only requiring 10\% fewer GFLOPs and 25\% fewer parameters in the semantic branch. Furthermore, a real-world test via our designed compact wearable panoptic segmentation system, indicates that our system based on the Panoptic Lintention Net accomplishes a relatively stable and exceptionally remarkable panoptic segmentation in real-world scenes.

Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Forschungsbericht/Preprint
Publikationsmonat/-jahr 03.2021
Sprache Englisch
Identifikator KITopen-ID: 1000138963
HGF-Programm 46.24.01 (POF IV, LK 01) Applied TA: Digitalizat. & Automat. Socio-Technical Change
Umfang 6 S.
Nachgewiesen in arXiv
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