This work proposes a graph mining based approach to mine a taxonomy of events from activities for complex videos which are represented in terms of qualitative spatio-temporal relat...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
In this paper, we model multi-agent events in terms of a temporally varying sequence of sub-events, and propose a novel approach for learning, detecting and representing events in...
We present a novel approach for highway traffic event detection. Our algorithm extracts features directly from the compressed video and automatically detects traffic events using ...
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...