Hyperspectral Semantic Segmentation

Propose a dataset which adopts multi-channel visual input. Source: Hyperspectral City

HSI-Drive is the hyperspectral image (HSI) dataset created by the Digital Electronics Design Group (GDED) of the University of the Basque Country (UPV/EHU). This database is intended to contribute to the research into the use of hyperspectral imaging for the development of advanced driver assistance systems (ADAS) and autonomous driving systems (ADS). The dataset contains a diverse set of images recorded with a small-size 25-band VNIR snapshot camera mounted on a moving automobile. The recordings have been made in different seasons of the year, at different day times, under different weather conditions and on different types of roads. The dataset contains images and videos classified and tagged accordingly to provide rich and diverse data.

We present datasets containing urban traffic and rural road scenes recorded using hyperspectral snap-shot sensors mounted on a moving car. The novel hyperspectral cameras used can capture whole spectral cubes at up to 15 Hz. This emerging new sensor modality enables hyperspectral scene analysis for autonomous driving tasks. Up to the best of the author’s knowledge no such dataset has been published so far. The datasets contain synchronized 3-D laser, spectrometer and hyperspectral data. Dense ground truth annotations are provided as semantic labels, material and traversability. The hyperspectral data ranges from visible to near infrared wavelengths. We explain our recoding platform and method, the associated data format along with a code library for easy data consumption. The datasets are publicly available for download.