TY - GEN
T1 - Glass object localization by joint inference of boundary and depth
AU - Wang, Tao
AU - He, Xuming
AU - Barnes, Nick
PY - 2012
Y1 - 2012
N2 - We address the problem of localizing glass objects with a multimodal RGB-D camera. Our method integrates the intensity and depth information from a single view point, and builds a Markov Random Field that predicts glass boundary and region jointly. Based on the localization, we also reconstruct the depth of the scene and fill in the missing depth values. The efficacy of our algorithm is validated on a new RGB-D Glass dataset of 43 distinct glass objects.
AB - We address the problem of localizing glass objects with a multimodal RGB-D camera. Our method integrates the intensity and depth information from a single view point, and builds a Markov Random Field that predicts glass boundary and region jointly. Based on the localization, we also reconstruct the depth of the scene and fill in the missing depth values. The efficacy of our algorithm is validated on a new RGB-D Glass dataset of 43 distinct glass objects.
UR - http://www.scopus.com/inward/record.url?scp=84874572202&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9784990644109
T3 - Proceedings - International Conference on Pattern Recognition
SP - 3783
EP - 3786
BT - ICPR 2012 - 21st International Conference on Pattern Recognition
T2 - 21st International Conference on Pattern Recognition, ICPR 2012
Y2 - 11 November 2012 through 15 November 2012
ER -