Multi-Object Tracking Analysis

Chiwoo Park () and Yu Ding ()
Additional contact information
Chiwoo Park: Florida State University
Yu Ding: Industrial & Systems Engineering

Chapter Chapter 10 in Data Science for Nano Image Analysis, 2021, pp 277-321 from Springer

Abstract: Abstract In situ microscopes are capable of imaging the transient dynamics of material processes at the nano-scale spatial resolution. The resulting material images contain the structures of material objects that change over the course of a material process. If one is interested in knowing how a population of material objects is collectively evolved in their sizes and shapes, a probability distribution function of the shapes and sizes ought to be tracked. Towards that objective, dynamic size distribution tracking is discussed in Chap. 7 , whereas dynamic shape distribution tracking is the focus of Chap. 8 . These distribution tracking methods are appropriate for characterizing the thermodynamic aspect of an overall material process, describing the behavior of a system containing a large number of material objects. But distribution tracking does not answer some other questions critical to material discovery, e.g., why do the size and shape distributions change as tracked, how do individual material objects evolve over time, and what type of chemical kinetics drives the evolution? If one is interested in explaining individualized evolutions or in learning the relationship between the chemical kinetics and the evolution process, then the temporal sequences of sizes, shapes, or other structural measures need to be tracked for individual material objects, in order to provide an in-depth analysis of the individual sequences. Such analysis is referred to as the multi-object tracking analysis. This chapter presents a detailed investigation on the topic of object tracking based on dynamic imaging measurements.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-72822-9_10

Ordering information: This item can be ordered from
http://www.springer.com/9783030728229

DOI: 10.1007/978-3-030-72822-9_10

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().