Abstract
In this work, different techniques of target tracking in video sequences have been studied. The aim is to decide whether the evaluated algorithms can be used to determine and analyze a special kind of trajectories. Different Feature Point Tracking Algorithms have been implemented. They solve the correspondence problem starting from a detected point set. After carrying out various experiments with synthetic and real points, we present an algorithm result assessment showing their adaptability in our problem: boar semen video sequences.
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References
Veenman, C.J., Reinders, M.J.T., Backer, E.: Resolving Motion Correspondence for Densely Moving. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 54–72 (2001)
Chetverikov, D., Verestóy, J.: Feature Point Tracking for Incomplete Trajectories. Image and Pattern Analysis Group, Budapest (1999)
Chetverikov, D., Verestóy, J.: Tracking feature points: A new algorithm. In: Proc. International Conf. on Pattern Recognition, pp. 1436–1438 (1998)
Nielsen, E.S., Tejera, M.H.: Seguimiento de Objetos Móviles usando la Distancia de Hausdorff. Departamento de Estadística, Investigación Operativa and Computación. Universidad de La Laguna, Tenerife (2000)
Shaw, G.L., Ramachandran, V.S.: Interpolation during apparent motion. Perception 11, 491–494 (1982)
Aggarwal, J.K., Davis, L.S., Martin, W.N.: Correspondence processes in dynamic scene analysis (1981)
Little, J.J., Bulthoff, H.H., Poggio, T.: Parallel optical flow using local voting. In: Proceedings of Second ICCV (1988)
Verestoy, J., Chetverikov, D.: Feature Point Tracking Algorithm. Image and Pattern Analysis Group, Budapest (1998), http://visual.ipan.sztaki.hu/psmweb/index.html
Rangarajan, K., Shah, M.: Establishing motion correspondence. In: CVGIP: Image Understanding, pp. 56–73 (1991)
Sethi, K., Jain, R.: Finding trajectories of feature points in a monocular image sequence. IEEE Trans. Pattern Analysis and Machine Intelligence PAMI-9(1), 56–73 (1987)
Barnard, S.T., Thompson, W.B.: Disparity analysis of images. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-2, 333–340 (1980)
Ullman, S.: The Interpretation of Visual Motion. Cambridge Press, Cambridge (1979)
Salari, V., Sethi, I.K.: Feature point correspondence in the presence of occlusion. IEEE Trans. Pattern Analysis and Machine Intelligence, 87–91 (1990)
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Robles, V., Alegre, E., Sebastian, J.M. (2004). Tracking Algorithms Evaluation in Feature Points Image Sequences. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_72
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DOI: https://doi.org/10.1007/978-3-540-30126-4_72
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