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Benchmark For Quantitative Evaluation Of Assisted Object Segmentation Methods To Image Sequences
Proceedings - 21st Brazilian Symposium On Computer Graphics And Image Processing, Sibgrapi 2008. , v. , n. , p. 95 - 102, 2008.
De Alencar Lotufo R.
Evaluation of segmentation methods applied to image sequences consists in the analysis of such methods according to quantitative and/or qualitative criteria, usually driven to some application. Literature proposes several metrics for quantitative evaluation of object segmentation methods to image sequences, but it is still considered an open problem, since no one of the proposed metrics is considered the standard one. More, as the best of our knowledge, there is no method in literature that does computational quantitative evaluation of assisted methods to object segmentation in image sequence. This paper introduces a benchmark to do such quantitative evaluation. This evaluation is done according to several criteria such as the robustness of segmentation and the easiness to segment the objects through the sequence. Experimental results also evaluates the robustness of the watershed from propagated markers technique. © 2008 IEEE.95102Falcão, A.X., Stolfi, J., Lotufo, R.A., The Image Foresting Transform: Theory, Algorithms and Applications (2004) IEEE Transactions on Pattern Analysis and Machine Intelligence, 26 (1), pp. 19-29. , JanuaryLucas, B., Kanade, T., An interative image registration technique with an application to stereo system (1981) Proceedings of DARPA Image Understanding Workshop, pp. 121-130Beucher, S., Meyer, F., Mathematical Morphology in Image Processing (1992) The Morphological Approach to Segmentation: The Watershed Transformation, pp. 433-481. , chapter 12, Marcel DekkerErden, C., Sankur, B., Tekalp, A., Performance Measures for Video Object Segmentation and Tracking (2004) IEEE Transactions on Image Processing, 13 (7), pp. 937-951. , JulyK. M. N.-P. D. D. Z. Ebrahimi. Evaluation of segmentation methods for surveillance applications. In EUSIPCO 2000, pages 1045-1048, Kobe, Japan, September 2000F. C. Flores and R. A. Lotufo. Watershed from Propagated Markers Improved by a Marker Binding Heuristic. In J. B. G.J.F. Banon and U. Braga-Neto, editors, Mathematical Morphology and its Applications to Image and Signal Processing, Proc. ISMM'07, pages 313-323. MCT/INPE, 2007Moscheni, F., Bhattacharjee, S., Kunt, M., Spatiotemporal Segmentation Based on Region Merging (1998) IEEE Transactions on Pattern Analysis and Machine Intelligence, 20 (9), pp. 897-915. , SeptemberFlores, F.C., Lotufo, R.A., Object Segmentation in Image Sequences by Watershed from Markers: A Generic Approach (2003) IEEE Proceedings of SIBGRAPI'2003, pp. 347-352. , Sao Carlos, Brazil, OctoberHe, Z., Dynamic programming framework for automatic video object segmentation and vision-assisted video preprocessing (2005) IEE Proceedings of Vision, Image and Signal Processing, pp. 597-603. , OctoberCorreia, P., Pereira, F., Objective Evaluation of Video Segmentation Quality (2003) IEEE Transactions on Image Processing, 12 (2), pp. 186-200. , FebruaryCorreia, P., Pereira, F., Video Object Relevance Metrics for Overall Segmentation Quality Evaluation (2006) EURASIP Journal on Applied Signal Processing, pp. 1-11. , Article ID 82915Salembier, P., Ruiz, J., On Filters by Reconstruction for Size and Motion Simplification (2002) Mathematical Morphology and its Applications to Image and Signal Processing, Proc. ISMM'02, pp. 425-434. , H. Talbot and R. Beare, editors, CSIRO PublishingSalembier, P., Marques, F., Pardas, M., Morros, J.R., Corset, I., Jeannin, S., Bouchard, L., Marcotegui, B., Segmentation-Based Video Coding System Allowing the Manipulation of Objects (1997) IEEE Transactions on Circuits and Systems for Video Technology, 7 (1), pp. 60-74. , FebruarySmith, P., Drummond, T., Cipolla, R., Layered Motion Segmentation and Depth Ordering by Tracking Edges (2004) IEEE Transactions on Pattern Analysis and Machine Intelligence, 26 (4), pp. 479-494. , AprilVillegas, P., Marichal, X., Perceptually-weighted evaluation criteria for segmentation masks in video sequences (2004) IEEE Transactions on Image Processing, 13 (8), pp. 1092-1103. , AugustMech, R., Marques, F., Objective Evaluation Criteria for 2-D Shape Estimation Results of Moving Objects (2002) EURASIP Journal on Applied Signal Processing, 2002, pp. 401-409