Abstract
Visual Place Recognition (VPR) is a fundamental task that allows a robotic platform to successfully localise itself in the environment. For decentralised VPR applications where the visual data has to be transmitted between several agents, the communication channel may restrict the localisation process when limited bandwidth is available. JPEG is an image compression standard that can employ high compression ratios to facilitate lower data transmission for VPR applications. However, when applying high levels of JPEG compression, both the image clarity and size are drastically reduced. In this paper, we incorporate sequence-based filtering in a number of well-established, learnt and non-learnt VPR techniques to overcome the performance loss resulted from introducing high levels of JPEG compression. The sequence length that enables 100% place matching performance is reported and an analysis of the amount of data required for each VPR technique to perform the transfer on the entire spectrum of JPEG compression is provided. Moreover, the time required by each VPR technique to perform place matching is investigated, on both uniformly and non-uniformly JPEG compressed data. The results show that it is beneficial to use a highly compressed JPEG dataset with an increased sequence length, as similar levels of VPR performance are reported at a significantly reduced bandwidth. The results presented in this paper also emphasize that there is a trade-off between the amount of data transferred and the total time required to perform VPR. Our experiments also suggest that is often favourable to compress the query images to the same quality of the map, as more efficient place matching can be performed. The experiments are conducted on several VPR datasets, under mild to extreme JPEG compression.
Abstract (translated)
视觉位置识别(VPR)是使机器人平台在环境中成功定位的基本任务。对于分散的VPR应用,视觉数据需要在多个代理之间传输,当有限的带宽可用时,通信通道可能会限制定位过程。JPEG是一种图像压缩标准,可以使用高压缩比来促进VPR应用较低的数据传输。然而,当应用采用高版本的JPEG压缩时,图像清晰度和大小都急剧下降。在本文中,我们将序列过滤纳入许多稳定且非学习的VPR技术中,以克服引入高版本的JPEG压缩所带来的性能损失。报道了能够实现100%位置匹配性能的序列长度,并对每个VPR技术在JPEG压缩光谱范围内的数据传输所需的数据量进行了分析。此外,我们还研究了每个VPR技术进行位置匹配所需的时间,在均匀和非均匀JPEG压缩的数据上进行了研究。结果表明,使用高压缩度的JPEG数据集和增加序列长度的选项 beneficial,因为相似的VPR性能在带宽显著减少的情况下出现。本文还强调,数据传输量与VPR总时间之间的权衡存在。我们的实验还表明,通常将查询图像压缩到地图质量相同的水平有利于进行更高效的位置匹配。在轻微的到极端的JPEG压缩条件下,对多个VPR数据集进行了实验。
URL
https://arxiv.org/abs/2302.13314
