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Issue No. 06 - June (2011 vol. 33)
ISSN: 0162-8828
pp: 1132-1146
Nicholas Constantine Makris , Massachusetts Institute of Technology, Cambridge
Berthold Klaus Paul Horn , Massachusetts Institute of Technology, Cambridge
Srinivasan Jagannathan , Massachusetts Institute of Technology, Cambridge
Purnima Ratilal , Northeastern University, Boston
We present methods for estimating forces which drive motion observed in density image sequences. Using these forces, we also present methods for predicting velocity and density evolution. To do this, we formulate and apply a Minimum Energy Flow (MEF) method which is capable of estimating both incompressible and compressible flows from time-varying density images. Both the MEF and force-estimation techniques are applied to experimentally obtained density images, spanning spatial scales from micrometers to several kilometers. Using density image sequences describing cell splitting, for example, we show that cell division is driven by gradients in apparent pressure within a cell. Using density image sequences of fish shoals, we also quantify 1) intershoal dynamics such as coalescence of fish groups over tens of kilometers, 2) fish mass flow between different parts of a large shoal, and 3) the stresses acting on large fish shoals.
Force estimation, density prediction, compressible flow estimation, minimum energy flow.
Nicholas Constantine Makris, Berthold Klaus Paul Horn, Srinivasan Jagannathan, Purnima Ratilal, "Force Estimation and Prediction from Time-Varying Density Images", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 33, no. , pp. 1132-1146, June 2011, doi:10.1109/TPAMI.2010.185
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