mlsanityData to 7 Oct 2026

SideSeeing: A multimodal dataset and collection of tools for sidewalk assessment

arXiv 2407.06464 ↗First posted 9 Jul 2024cs.CV cs.CYcited by 1

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Abstract (arXiv)

This paper introduces SideSeeing, a novel initiative that provides tools and datasets for assessing the built environment. We present a framework for street-level data acquisition, loading, and analysis. Using the framework, we collected a novel dataset that integrates synchronized video footaged captured from chest-mounted mobile devices with sensor data (accelerometer, gyroscope, magnetometer, and GPS). Each data sample represents a path traversed by a user filming sidewalks near hospitals in Brazil and the USA. The dataset encompasses three hours of content covering 12 kilometers around nine hospitals, and includes 325,000 video frames with corresponding sensor data. Additionally, we present a novel 68-element taxonomy specifically created for sidewalk scene identification. SideSeeing is a step towards a suite of tools that urban experts can use to perform in-depth sidewalk accessibility evaluations. SideSeeing data and tools are publicly available at https://sites.usp.br/sideseeing/.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 30 references that are in the map. First posted on arXiv 9 Jul 2024.

Builds on

5 of 30 references.

References · 5

  1. 2022CitySurfaces: City-Scale Semantic Segmentation of Sidewalk Materialscited by 8
  2. 2020Urban Mosaic: Visual Exploration of Streetscapes Using Large-Scale Image Datacited by 7
  3. 2024The State of the Art in Visual Analytics for 3D Urban Datacited by 4
  4. 2022Urban Rhapsody: Large-scale exploration of urban soundscapescited by 3
  5. 2023OASIS: Automated Assessment of Urban Pedestrian Paths at Scalecited by 2

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