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A simplified ICA-based local similarity stereo matching / Suting Chen in The Visual Computer, vol 37 n° 2 (February 2021)  

Public [article]  inThe Visual Computer > vol 37 n° 2 (February 2021) . - pp 411 - 419 Titre : A simplified ICA-based local similarity stereo matching Type de document : Article/Communication Auteurs : Suting Chen, Auteur ; Jinglin Zhang, Auteur ; Meng Jin, Auteur Année de publication : 2021 Article en page(s) : pp 411 - 419 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse en composantes indépendantes [Termes IGN] appariement d'images [Termes IGN] similitude Résumé : (auteur) Since the existing stereo matching methods may fail in the regions of non-textures, boundaries and tiny details, a simplified independent component correlation algorithm (ICA)-based local similarity stereo matching algorithm is proposed. In order to improve the DispNetC, the proposed algorithm first offers the simplified independent component correlation algorithm (SICA) cost aggregation. Then, the algorithm introduces the matching cost volume pyramid, which simplifies the pre-processing process for the ICA. Also, the SICA loss function is defined. Next, the region-wise loss function combined with the pixel-wise loss function is defined as a local similarity loss function to improve the spatial structure of the disparity map. Finally, the SICA loss function is combined with the local similarity loss function, which is defined to estimate the disparity map and to compensate the edge information of the disparity map. Experimental results on KITTI dataset show that the average absolute error of the proposed algorithm is about 37% lower than that of the DispNetC, and its runtime consuming is about 0.6 s lower than that of GC-Net. Numéro de notice : A2021-176 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-020-01811-x Date de publication en ligne : 15/02/2020 En ligne : https://doi.org/10.1007/s00371-020-01811-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97286 [article]