Title

Motion Trajectories

Abstract

A simple algorithm for selecting and linking interesting flow vectors across a sequence of frames for computing motion trajectories is presented. Tokens are tracked that have both interesting pixel gray values in the spatial domain and in the optical flow field in the temporal domain. This and operation effectively remove some redundant trajectories. Due to errors introduced during the computation of optical flow, and the linking of such flow vectors across a sequence of frames, the resultant trajectories are not always smooth. A Kaiman filtering based approach is discussed for smoothing the trajectories. Isolating the trajectories into sets belonging to individual objects is an important first step that should be taken before any type of shape or motion interpretation can be done. Therefore, a simple algorithm for segmenting motion trajectories is also discussed. When motion trajectories belonging to a single translating object are extended, they intersect at a single point called the focus of expansion (FOE). If the motions of objects are assumed to be independent, each FOE represents one object. Therefore, FOE can be used to segment trajectories belonging to individual objects. A simple but highly robust algorithm for partitioning motion trajectories is presented that does not require the exact location of FOE, but uses some useful properties of FOE. The authors have applied their method for computing and segmenting motion trajectories to a number of real sequences, and have obtained very encouraging results. © 1993 IEEE

Publication Date

1-1-1993

Publication Title

IEEE Transactions on Systems, Man and Cybernetics

Volume

23

Issue

4

Number of Pages

1138-1150

Document Type

Article

Identifier

scopus

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/21.247894

Socpus ID

0027631927 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0027631927

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