Content-based retrieval using trajectories of moving objects in video databases

Abstract

In this paper, we propose a new spatio-temporal representation scheme for modeling multiple moving objects' trajectories in video databases. For contentbased video retrieval on moving objects efficiently, our representation scheme considers the moving distance of an object during a given time interval as well as its temporal and spatial relationships. We present a similarity measure algorithm for the multiple moving objects' trajectories.

Motion-based behaviour learning, profiling and classification in the presence of anomalies

“…Previous work has sought to represent moving object trajectories through a wide variety of direction schemes, polynomial models and other function approximations [1][2][3][4]7,[15][16][17][18]. It is surprising to find that many of these candidate time series indexing schemes have not yet been applied to the problem of motion data mining and trajectory clustering.…”

Classifying spatiotemporal object trajectories using unsupervised learning in the coefficient feature space

“…Much of the earlier research focus has been on highlevel object trajectory representation schemes that are able to produce compressed forms of motion data [1,3,4,10,13,16,22,23,29,34,35]. This work presupposes the existence of some low-level visual tracking scheme for reliably extracting object-based trajectories [17,37].…”

Behavior Recognition Using any Feature Space Representation of Motion Trajectories

“…For example, Discrete Fourier Transforms (DFT) (Faloutsos et al, 1994), Discrete Wavelet Transforms (DWT) (Chan & Fu, 1999), Adaptive Piecewise Constant Approximations (APCA) (Keogh et al, 2001), and Chebyshev polynomials (Cai & Ng, 2004) have been used to conduct similarity search in time series data. Previous work has also sought to represent moving object trajectories through piecewise linear or quadratic interpolation functions (Chang et al, 1998;Jeanin & Divakaran, 2001), motion histograms (Aghbari et al, 2003) or discretised direction-based schemes (Dagtas et al, 2000;Shim & Chang, 2001;. Spatiotemporal representations using piecewise-defined polynomials were proposed by (Hsu & Teng, 2002), although consistency in applying a trajectory-splitting scheme across query and searched trajectories can be problematic.…”