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Automated tracking methods greatly expedite the collection of data for studying social insects. However, due to the frequency of occlusions (due to interactions) and similarity in appearance and motion features, tracking could easily drift to the incorrect object as the affinity model is unable to discern between similar objects. Recently, a method to filter incorrect associations based on areas of...
The tracking of ants in video is important for the analysis of their complex group behavior. However, the manual analysis of these videos is tedious and time consuming. Automated tracking methods tend to drift due to frequent occlusions during their interactions and similarity in appearance. Semi-automated tracking methods enable corrections of tracking errors by incorporating user interaction. Although...
The automated tracking of social insects, such as ants, can efficiently provide unparalleled amounts of data for the of study complex group behaviors. However, a high level of occlusion along with similarity in appearance and motion can cause the tracking to drift to an incorrect ant. In this paper, we reduce drifting by using occlusion to identify incorrect ants and prevent the tracking from drifting...
Many feature transforms have been proposed for the problem of trajectory matching. These methods, which are often based on shape matching, tend to perform poorly for biological trajectories, such as cell motion, because similar biological behavior often results in dissimilar trajectory shape. Additionally, the criteria used for similarity may differ depending on the user's particular interest or the...
The automated tracking of social insects, such as ants, could dramatically increase the fidelity and amount of analyzed data for studying complex group behaviors. Recently, data association based multiple object tracking methods have shown promise in improving handling of occlusions. However, the tracking of ants in a colony is still challenging as (1) their motion is often sporadic and irregular...
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