%0 Conference Paper %1 Palou2012h %A Palou, Guillem %A Salembier, Philippe %B 2012 IEEE ICASSP %D 2012 %K imported %P 793--796 %R 10.1109/ICASSP.2012.6288003 %T From local occlusion cues to global monocular depth estimation %U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6288003&contentType=Conference+Publications&matchBoolean=true&searchField=Search\_All&queryText=(palou+monocular) %X In this paper, we propose a system to obtain a depth ordered segmentation of a single image based on low level cues. The algorithm first constructs a hierarchical, region-based image representation of the image using a Binary Partition Tree (BPT). During the building process, T-junction depth cues are detected, along with high convex boundaries. When the BPT is built, a suitable segmentation is found and a global depth ordering is found using a probabilistic framework. Results are compared with state of the art depth ordering and figure/ground labeling systems. The advantage of the proposed approach compared to systems based on a training procedure is the lack of assumptions about the scene content. Moreover, it is shown that the system outperforms previously low-level cue based systems, while offering similar results to a priori trained figure/ground labeling algorithms. %@ 978-1-4673-0046-9

@inproceedings{Palou2012h, abstract = {In this paper, we propose a system to obtain a depth ordered segmentation of a single image based on low level cues. The algorithm first constructs a hierarchical, region-based image representation of the image using a Binary Partition Tree (BPT). During the building process, T-junction depth cues are detected, along with high convex boundaries. When the BPT is built, a suitable segmentation is found and a global depth ordering is found using a probabilistic framework. Results are compared with state of the art depth ordering and figure/ground labeling systems. The advantage of the proposed approach compared to systems based on a training procedure is the lack of assumptions about the scene content. Moreover, it is shown that the system outperforms previously low-level cue based systems, while offering similar results to a priori trained figure/ground labeling algorithms.}, added-at = {2013-09-29T14:16:50.000+0200}, author = {Palou, Guillem and Salembier, Philippe}, biburl = {https://www.bibsonomy.org/bibtex/21acf8400cd785e09b6bbf2c23be581d9/guillem.palou}, booktitle = {2012 IEEE ICASSP}, doi = {10.1109/ICASSP.2012.6288003}, file = {:Users/guillem/Documents/Doctorat/Bibliografia/articles/Palou, Salembier\_2012\_From local occlusion cues to global monocular depth estimation.pdf:pdf}, interhash = {13b05329cbdbea5d70974f24483c7f6b}, intrahash = {1acf8400cd785e09b6bbf2c23be581d9}, isbn = {978-1-4673-0046-9}, keywords = {imported}, pages = {793--796}, timestamp = {2013-09-29T14:16:50.000+0200}, title = {{From local occlusion cues to global monocular depth estimation}}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=\&arnumber=6288003\&contentType=Conference+Publications\&matchBoolean=true\&searchField=Search\_All\&queryText=(palou+monocular)}, year = 2012 }