Bioluminescence imaging (BLI) offers the possibility to study and image biology at molecular scale in small animals with applications in oncology or gene expression studies. Here we present a novel model-based approach to 3D animal tracking from monocular video which allows the quantification of bioluminescence signal on freely moving animals. The 3D animal pose and the illumination are dynamically estimated through minimization of an objective function with constraints on the bioluminescence signal position. Derived from an inverse problem formulation, the objective function enables explicit use of temporal continuity and shading information, while handling important self-occlusions and time-varying illumination. In this model-based framework, we include a constraint on the 3D position of bioluminescence signal to enforce tracking of the biologically produced signal. The minimization is done efficiently using a quasi-Newton method, with a rigorous derivation of the objective function gradient. Promising experimental results demonstrate the potentials of our approach for 3D accurate measurement with freely moving animal. © 2010 Springer-Verlag.
CITATION STYLE
Savinaud, M., De La Gorce, M., Maitrejean, S., & Paragios, N. (2010). Model-based multi-view fusion of cinematic flow and optical imaging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6362 LNCS, pp. 668–675). Springer Verlag. https://doi.org/10.1007/978-3-642-15745-5_82
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