TY - GEN

T1 - Dynamics-aware similarity of moving objects trajectories

AU - Trajcevski, Goce

AU - Ding, Hui

AU - Scheuermann, Peter

AU - Tamassia, Roberto

AU - Vaccaro, Dennis

PY - 2007/12/1

Y1 - 2007/12/1

N2 - This work addresses the problem of obtaining the degree of similarity between trajectories of moving objects. Typically, a Moving Objects Database (MOD) contains sequences of (location, time) points describing the motion of individual objects, however, they also implicitly storethe velocity - an important attribute describing the dynamics the motion. Our main goal is to extend the MOD capability with reasoning about how similar are the trajectories of objects, possibly moving along geographically different routes. We use a distance function which balances the lack of temporal-awareness of the Hausdorff distance with the generality (and complexity of calculation) of the Fréchet distance. Based on the observation that in practice the individual segments of trajectories are assumed to have constant speed, we provide efficient algorithms for: (1) optimal matching between trajectories; and (2) approximate matching between trajectories, both under translations and rotations, where the approximate algorithm guarantees a bounded error with respect to the optimal one.

AB - This work addresses the problem of obtaining the degree of similarity between trajectories of moving objects. Typically, a Moving Objects Database (MOD) contains sequences of (location, time) points describing the motion of individual objects, however, they also implicitly storethe velocity - an important attribute describing the dynamics the motion. Our main goal is to extend the MOD capability with reasoning about how similar are the trajectories of objects, possibly moving along geographically different routes. We use a distance function which balances the lack of temporal-awareness of the Hausdorff distance with the generality (and complexity of calculation) of the Fréchet distance. Based on the observation that in practice the individual segments of trajectories are assumed to have constant speed, we provide efficient algorithms for: (1) optimal matching between trajectories; and (2) approximate matching between trajectories, both under translations and rotations, where the approximate algorithm guarantees a bounded error with respect to the optimal one.

KW - dynamics

KW - similarity

KW - trajectories

UR - http://www.scopus.com/inward/record.url?scp=52949127470&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=52949127470&partnerID=8YFLogxK

U2 - 10.1145/1341012.1341027

DO - 10.1145/1341012.1341027

M3 - Conference contribution

AN - SCOPUS:52949127470

SN - 9781595939142

T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

SP - 75

EP - 82

BT - Proceedings of the 15th ACM International Symposium on Advances in Geographic Information Systems, GIS 2007

T2 - 15th ACM International Symposium on Advances in Geographic Information Systems, GIS 2007

Y2 - 7 November 2007 through 9 November 2007

ER -