Neural Information Processing Systems http://nips.cc/

Min-cost flow has been a widely used paradigm for solving data association problems in multi-object tracking (MOT). However, most existing methods of solving min-cost flow problems in MOT are either direct adoption or slight modifications of generic min-cost flow algorithms, yielding sub-optimal computation efficiency and holding the applications back from larger scale of problems. In this paper, by exploiting the special structures and properties of the graphs formulated in MOT problems, we develop an efficient min-cost flow algorithm, namely, minimumupdate Successive Shortest Path (muSSP).

Dynamic time warping (DTW) is a fundamental technique in time series analysis for comparing one curve to another using a flexible time-warping function. However, it was designed to compare a single pair of curves. In many applications, such as in metabolomics and image series analysis, alignment is simultaneously needed for multiple pairs. Because the underlying warping functions are often related, independent application of DTW to each pair is a sub-optimal solution. Yet, it is largely unknown how to efficiently conduct a joint alignment with all warping functions simultaneously considered, since any given warping function is constrained by the others and dynamic programming cannot be applied.