Accurately identifying corresponded landmarks from a
population of shape instances is the major challenge in
constructing statistical shape models. In general, shapecorrespondenc...
In this paper we introduce a novel method to detect and
localize abnormal behaviors in crowd videos using Social
Force model. For this purpose, a grid of particles is placed
ove...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
Cross-domain learning methods have shown promising
results by leveraging labeled patterns from auxiliary domains
to learn a robust classifier for target domain, which
has a limi...
Dong Xu, Ivor Wai-Hung Tsang, Lixin Duan, Stephen ...
Extremely crowded scenes present unique challenges to
video analysis that cannot be addressed with conventional
approaches. We present a novel statistical framework for
modeling...
Louis Kratz (Drexel University), Ko Nishino (Drexe...