IFTrace: Video segmentation of deformable objects using the Image Foresting Transform

Autor(es)

Minetto, R. ^[1] ; Spina, T. V. ^[1] ; Falcao, A. X. ^[1] ; Leite, N. J. ^[1] ; Papa, J. P. ^[2] ; Stolfi, J. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas, UNICAMP, Inst Comp, Campinas, SP - Brazil

^[2] Univ Estadual Paulista, Dept Comp, Bauru - Brazil

• Tipo de documento: Artigo Científico
• Fonte: COMPUTER VISION AND IMAGE UNDERSTANDING; v. 116, n. 2, p. 274-291, FEB 2012.
• Citações Web of Science: 4

Resumo

We introduce IFTrace, a method for video segmentation of deformable objects. The algorithm makes minimal assumptions about the nature of the tracked object: basically, that it consists of a few connected regions, and has a well-defined border. The objects to be tracked are interactively segmented in the first frame of the video, and a set of markers is then automatically selected in the interior and immediate surroundings of the object. These markers are then located in the next frame by a combination of KLT feature finding and motion extrapolation. Object boundaries are then identified from these markers by the Image Foresting Transform (IFT). These steps are repeated for all subsequent frames until the end of the movie. Thanks to the IFT and a special boundary detection operator, IFTrace can reliably track deformable objects in the presence of partial and total occlusions, camera motion, lighting and color changes, and other complications. Tests on real videos show that the IFT is better suited to this task than Graph-Cut methods, and that IFTrace is more robust than other state-of-the art algorithms - namely, the OpenCV Snake and Cam-Shift algorithms, Hess's Particle-Filter, and Zhong and Chang's method based on spatio-temporal consistency. (C) 2011 Elsevier Inc. All rights reserved. (AU)

• Processo FAPESP: 07/52015-0 - Métodos de aproximação para computação visual
• Beneficiário: Jorge Stolfi
• Linha de fomento: Auxílio à Pesquisa - Temático
• Processo FAPESP: 09/11908-8 - Edição interativa de imagens naturais baseada na transformada imagem-floresta
• Beneficiário: Thiago Vallin Spina
• Linha de fomento: Bolsas no Brasil - Mestrado
• Processo FAPESP: 07/54201-6 - Análise de vídeos digitais: problemas de segmentação espaço-temporal, detecção de movimentos baseados em fluxo ótico e seleção de frames representativos
• Beneficiário: Rodrigo Minetto
• Linha de fomento: Bolsas no Brasil - Doutorado