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In this paper we present a new procedure for tracking bi-directional objects in kymographs. The proposed technique is based on a novel adaptive and directional band-pass filtering method which allows us to separate particles which move in opposite directions. The filtering method exploits the curvelet analysis of the kymograph image to automatically adapt to the objects trails characteristics and...
Particle detection and tracking methods generally assume a simplistic image model that is rarely valid when imaging biological processes in fluorescence microscopy. The tracking task may become nearly impossible when complex biological structures are visible and interfere with the signal of interest. To address this limitation we have adapted a source separation technique based on sparsity principles...
Multiple hypothesis tracking (MHT) is a preferred technique for solving the data association problem in modern multiple target tracking systems. However in bioimaging applications, its use has long been thought impossible due to the prohibitive cost induced by the high number of objects that need to be tracked and the poor quality of images. We show in this paper that this broadly accepted view should...
We present a new feature-aided tracking algorithm dedicated to the task of tracking multiple and closely-spaced biological particles. We propose a new function to score associations, based on kinetic models, and enriched with an additional feature. This feature is based on adaptive profiles and the physical properties of the acquisition system. A key property is that this feature definition allows...
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