Region-based image and video processing

Type Start End
Internal Jan 1992 Dec 2020
Responsible URL

Publications

Sánchez-Escué J. Bundling interest points for object classification Ventura C, Giró-i-Nieto X. 2014 . (2.15 MB)
Tochon G, Feret JB, Valero S, Martin RE, Tupayachi R, Chanussot J, Salembier P, Asner G. Segmentation hyperspectrales de forets tropicales par arbres de partition binaires. Revue française de photogrammétrie et de télédétection. 2013 ;202(1):55-65. (2.51 MB)
Alonso-González A, Valero S, Chanussot J, López-Martínez C, Salembier P. Processing Multidimensional SAR and Hyperspectral Images With Binary Partition Tree. Proceedings of the IEEE. 2013 ;101(3):723 - 747. (4.46 MB)
Valero S, Salembier P, Chanussot J. Hyperspectral image representation and processing with Binary Partition Trees. IEEE Transactions on Image Processing. 2013 ;22(4):1430 - 1443. (1.81 MB)
Palou G, Salembier P. Monocular Depth Ordering Using T-junctions and Convexity Occlusion Cues. IEEE Transactions on Image Processing. 2013 ;22(5): 1926 - 1939 . (2.64 MB)
Salvador A, Carlier A, Giró-i-Nieto X, Marques O, Charvillat V. Crowdsourced Object Segmentation with a Game. In: ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Barcelona; 2013. (1.22 MB)
Valero S, Salembier P, Chanussot J. Object recognition in urban hyperspectral images using binary partition tree representation. In: IEEE International Geoscience and Remote Sensing Symposium, IGARSS'2013. IEEE International Geoscience and Remote Sensing Symposium, IGARSS'2013. Melbourne, Australia: IEEE; 2013. (498.43 KB)
Salvador A. Crowdsourced Object Segmentation with a Game Giró-i-Nieto X, Carlier A, Charvillat V, Marques O. 2013 . (1.34 MB)
Palou G, Salembier P. Depth Ordering on Image Sequences Using Motion Occlusions. In: IEEE Int. Conf. in Image Processing, ICIP 2012. IEEE Int. Conf. in Image Processing, ICIP 2012. Orlando, Florida, USA; 2012. (5.42 MB)
Giró-i-Nieto X. Part-Based Object Retrieval With Binary Partition Trees. In: Doctoral Consortium in Computer Vision and Pattern Recognition (CVPR). Doctoral Consortium in Computer Vision and Pattern Recognition (CVPR). Providence (RI), USA: IEEE Computer Society; 2012. (993.04 KB)

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