@inproceedings{kundu2016feature,
author = {Kundu, Abhijit and Vineet, Vibhav and Koltun, Vladlen},
title = {Feature Space Optimization for Semantic Video Segmentation},
year = {2016},
month = {July},
abstract = {We present an approach to long-range spatio-temporal regularization in semantic video segmentation. Temporal regularization in video is challenging because both the camera and the scene may be in motion. Thus Euclidean distance in the space-time volume is not a good proxy for correspondence. We optimize the mapping of pixels to a Euclidean feature space so as to minimize distances between corresponding points. Structured prediction is performed by a dense CRF that operates on the optimized features. Experimental results demonstrate that the presented approach increases the accuracy and temporal consistency of semantic video segmentation.},
url = {http://approjects.co.za/?big=en-us/research/publication/feature-space-optimization-for-semantic-video-segmentation/},
}