Tracking feature points in time-varying images using an opportunistic selection approach
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Cited by (33)
Sperm motility analysis system implemented on a hybrid architecture to produce an intelligent analyzer
2020, Informatics in Medicine UnlockedCitation Excerpt :Various tracking methods are proposed and applied in different CASA systems. Optical flows, matching feature points in two frames using a hypothesis testing method [29,30], opportunistic selection strategy [31], Pool's method [32], real-time spermatozoa tracing system (RSTS) [14], principal component analysis [33,34], watershed segmentation, and frame difference methods are some examples of techniques. These methods were compared previously [35].
Gaussian and Laplacian of Gaussian weighting functions for robust feature based tracking
2005, Pattern Recognition LettersIdentifying truck correspondence in multi-frame imagery
2005, Transportation Research Part C: Emerging TechnologiesMotion tracking as a constrained optimization problem
2003, Pattern RecognitionEstablishing motion correspondence using extended temporal scope
2003, Artificial IntelligenceA relaxation algorithm for real-time multiple view 3D-tracking
2002, Image and Vision ComputingCitation Excerpt :Typically isolated objects are tracked using a Kalman filter approach to predict and update object location estimates from observations [26,48]. Previous work, such as Refs. [17–19], focuses on the cost function definition according to motion smoothness or geometric constraints taking into account object occlusion and reappearance. Techniques for statistical data association have also been applied to motion correspondence [26,27].