TY - GEN
T1 - 3D model-based sematic labeling of 2D objects
AU - Petre, Raluca Diana
AU - Zaharia, Titus
PY - 2011/12/1
Y1 - 2011/12/1
N2 - This paper tackles the issue of still image object categorization. The objective is to infer the semantics of 2D objects present in natural images. The principle of the proposed approach consists of exploiting categorized 3D synthetic models in order to identify unknown 2D objects, based on 2D/3D matching techniques. Notably, we use 2D/3D shape indexing methods, where 3D models are described through a set of 2D views. Experimental results carried out on both MPEG-7 and Princeton 3D mesh test sets show recognition rates of up to 89%.
AB - This paper tackles the issue of still image object categorization. The objective is to infer the semantics of 2D objects present in natural images. The principle of the proposed approach consists of exploiting categorized 3D synthetic models in order to identify unknown 2D objects, based on 2D/3D matching techniques. Notably, we use 2D/3D shape indexing methods, where 3D models are described through a set of 2D views. Experimental results carried out on both MPEG-7 and Princeton 3D mesh test sets show recognition rates of up to 89%.
KW - 2D/3D shape descriptors
KW - 3D mesh
KW - indexing and retrieval
KW - object classification
UR - https://www.scopus.com/pages/publications/84856992713
U2 - 10.1109/DICTA.2011.32
DO - 10.1109/DICTA.2011.32
M3 - Conference contribution
AN - SCOPUS:84856992713
SN - 9780769545882
T3 - Proceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011
SP - 152
EP - 157
BT - Proceedings - 2011 International Conference on Digital Image Computing
T2 - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011
Y2 - 6 December 2011 through 8 December 2011
ER -