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 Section Demos/COLL

Collaborative tracking


In the clips below the results of a new collaborative tracking approach are presented. Using this technique it is possible to continuously estimate the position and the appearance model of the trackers also during occlusion. The reported experimental results demonstrate the performance improvements that can be obtained using the collaborative approach over the independent one, both for position and shape estimation.

Results


Sequence 1

Sequence 1

Collaborative AVI

Non collaborative AVI

Sequence 2

Sequence 2

Collaborative AVI

Non collaborative AVI

Sequence 3

Sequence 3

Collaborative AVI

Non collaborative AVI

Sequence 4

Sequence 4

Collaborative AVI

Sequence 5

Sequence 5

Collaborative AVI

Sequence 7

Sequence 7

Collaborative AVI

print

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 News
New accepted papers:

M. Ravanbakhsh, M. Nabi, E. Sangineto, L. Marcenaro, C.S. Regazzoni, and N. Sebe, "Abnormal Event Detection in Videos using Generative Adversarial Nets", 24th IEEE International Conference on Image Processing (ICIP). 17-20 September 2017, Beijing, China

D. Campo, M. Baydoun, L. Marcenaro, and C.S. Regazzoni, "Task-dependent saliency estimation from trajectories of agents in video sequences", 24th IEEE International Conference on Image Processing (ICIP). 17-20 September 2017, Beijing, China

M.O. Mughal, L. Marcenaro, and C.S. Regazzoni, "Energy Detection in Multi-user Relay Networks", Wireless Personal Communications (2017): 1-10

A. Mazzú, P. Morerio, L. Marcenaro, C.S. Regazzoni, "A Cognitive Control-inspired approach to Object Tracking", IEEE Transactions on Image Processing

V. Bastani, L. Marcenaro, C.S. Regazzoni, "Online Nonparametric Bayesian Activity Mining and Analysis From Surveillance Video", IEEE Transactions on Image Processing


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