視覚障害者向けナビゲーション知覚のためのPanoptic Lintentionネットワーク
Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually Impaired
線形時間・線形空間で長距離相互作用をモデル化するLintention注意機構を提案し、それを用いたパノプティックセグメンテーションモデルで視覚障害者の歩行支援を効率化した。
著者: Wei Mao, Jiaming Zhang, Kailun Yang, Rainer Stiefelhagen
分類: cs.CV, cs.LG, cs.RO, eess.IV
原文アブストラクト
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.
