Behavior and trajectory analysis in multicamera settings
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A bottom-up approach for human behaviour understanding is presented, using a multi-camera system.
- The proposed methodology classifies behaviour as normal or abnormal, by treating short-term behaviour classification and trajectory classification as two different classification problems.
- Based on that assumption, a set of calculated features provide input to two one-class classifiers: a Support Vector Machine and a continuous Hidden Markov Model treated as an one-class classifier
- The superposition of foreground object projections on a common plane may create artifacts which can seriously disorientate a human detector by creating false positives. We present a method which eliminates those artifacts by using only geometrical information thus contributing to robust human detection for multiple views.
