Log In Sign Up

Angular Luminance for Material Segmentation

by   Jia Xue, et al.

Moving cameras provide multiple intensity measurements per pixel, yet often semantic segmentation, material recognition, and object recognition do not utilize this information. With basic alignment over several frames of a moving camera sequence, a distribution of intensities over multiple angles is obtained. It is well known from prior work that luminance histograms and the statistics of natural images provide a strong material recognition cue. We utilize per-pixel angular luminance distributions as a key feature in discriminating the material of the surface. The angle-space sampling in a multiview satellite image sequence is an unstructured sampling of the underlying reflectance function of the material. For real-world materials there is significant intra-class variation that can be managed by building a angular luminance network (AngLNet). This network combines angular reflectance cues from multiple images with spatial cues as input to fully convolutional networks for material segmentation. We demonstrate the increased performance of AngLNet over prior state-of-the-art in material segmentation from satellite imagery.


page 2

page 4


Material Segmentation of Multi-View Satellite Imagery

Material recognition methods use image context and local cues for pixel-...

Reflectance Hashing for Material Recognition

We introduce a novel method for using reflectance to identify materials....

Differential Viewpoints for Ground Terrain Material Recognition

Computational surface modeling that underlies material recognition has t...

Differential Angular Imaging for Material Recognition

Material recognition for real-world outdoor surfaces has become increasi...

Improving Building Segmentation for Off-Nadir Satellite Imagery

Automatic building segmentation is an important task for satellite image...

Insights From A Large-Scale Database of Material Depictions In Paintings

Deep learning has paved the way for strong recognition systems which are...

Decoupling Respiratory and Angular Variation in Rotational X-ray Scans Using a Prior Bilinear Model

Data-driven respiratory signal extraction from rotational X-ray scans ha...