TY - GEN
T1 - Tracking multiple ants in a colony
AU - Fasciano, Thomas
AU - Nguyen, Hoan
AU - Dornhaus, Anna
AU - Shin, Min C.
PY - 2013
Y1 - 2013
N2 - The automated tracking of social insects, such as ants, could dramatically increase the fidelity and amount of analyzed data for studying complex group behaviors. Recently, data association based multiple object tracking methods have shown promise in improving handling of occlusions. However, the tracking of ants in a colony is still challenging as (1) their motion is often sporadic and irregular and (2) they are mostly present the entire duration of video. In this paper, we propose to improve the data association based tracking of multiple ants. First, we model the ant's motion using a set of irregular motion features including random walk model. Second, we use the convergence of particle filter based tracking to match tracklets with a long temporal gap. Testing results of two-fold cross validation on a 10,000 frame video shows that our proposed method was able to reduce the number of fragments by 61% and ID switches by 57%.
AB - The automated tracking of social insects, such as ants, could dramatically increase the fidelity and amount of analyzed data for studying complex group behaviors. Recently, data association based multiple object tracking methods have shown promise in improving handling of occlusions. However, the tracking of ants in a colony is still challenging as (1) their motion is often sporadic and irregular and (2) they are mostly present the entire duration of video. In this paper, we propose to improve the data association based tracking of multiple ants. First, we model the ant's motion using a set of irregular motion features including random walk model. Second, we use the convergence of particle filter based tracking to match tracklets with a long temporal gap. Testing results of two-fold cross validation on a 10,000 frame video shows that our proposed method was able to reduce the number of fragments by 61% and ID switches by 57%.
UR - http://www.scopus.com/inward/record.url?scp=84875611875&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875611875&partnerID=8YFLogxK
U2 - 10.1109/WACV.2013.6475065
DO - 10.1109/WACV.2013.6475065
M3 - Conference contribution
AN - SCOPUS:84875611875
SN - 9781467350532
T3 - Proceedings of IEEE Workshop on Applications of Computer Vision
SP - 534
EP - 540
BT - 2013 IEEE Workshop on Applications of Computer Vision, WACV 2013
T2 - 2013 IEEE Workshop on Applications of Computer Vision, WACV 2013
Y2 - 15 January 2013 through 17 January 2013
ER -