A multiple object tracking system applied to insect behavior

Segmentation and tracking of multiple objects is an extensively researched field among Image Sciences. Multiple object tracking is, in general, a very hard problem due to the great number of potencial issues that might arise (such as the sudden movement of the tracked objects, changes on the appearence of either the tracked objects or the background scene, bad-quality frames, occlusion between an object and the scene or between multiple objects, or camera movement). Normally, object tracking is performed on applications that require the object locations to perform calculations later. This paper describes the research, design and development of a system created in order to track multiple insects on recorded videos.

[1]  S. Benhamou How to reliably estimate the tortuosity of an animal's path: straightness, sinuosity, or fractal dimension? , 2004, Journal of theoretical biology.

[2]  J. MacQueen Some methods for classification and analysis of multivariate observations , 1967 .

[3]  Miguel Amável Pinheiro Multi-object tracking in video sequences , 2010 .

[4]  David Eppstein,et al.  Fast optimal parallel algorithms for maximal matching in sparse graphs , 1992 .

[5]  Nasser Kehtarnavaz,et al.  Real-Time Imaging VI , 2002 .

[6]  Katsushi Ikeuchi,et al.  INCIDENT DETECTION AT INTERSECTIONS UTILIZING HIDDEN MARKOV MODEL , 1999 .

[7]  A. Crespi,et al.  Tracking Individuals Shows Spatial Fidelity Is a Key Regulator of Ant Social Organization , 2013, Science.

[8]  Guo Li,et al.  Tracking video objects with feature points based particle filtering , 2010, Multimedia Tools and Applications.

[9]  S. Satoh,et al.  Human action recognition in crowded surveillance video sequences by using features taken from key-point trajectories , 2011, CVPR 2011 WORKSHOPS.

[10]  Francois Bremond,et al.  An object tracking in particle filtering and data association framework, using SIFT features , 2011, ICDP.

[11]  Roland T. Chin,et al.  On the Detection of Dominant Points on Digital Curves , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Johnson I. Agbinya,et al.  Multi-Object Tracking in Video , 1999, Real Time Imaging.

[13]  Keiichi Abe,et al.  Topological structural analysis of digitized binary images by border following , 1985, Comput. Vis. Graph. Image Process..

[14]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Bodo Manthey,et al.  k-Means Has Polynomial Smoothed Complexity , 2009, 2009 50th Annual IEEE Symposium on Foundations of Computer Science.

[16]  Antonio Torralba,et al.  Unsupervised Detection of Regions of Interest Using Iterative Link Analysis , 2009, NIPS.

[17]  Manuela M. Veloso,et al.  Automatically tracking and analyzing the behavior of live insect colonies , 2001, AGENTS '01.