Towards Multi-View Object Class Detection
Alexander Thomas, Vittorio Ferrari, Bastian Leibe, Tinne Tuytelaars, Bernt Schiele, Luc Van Gool and Luc Van Gool
In: IEEE Conference on Computer Vision and Pattern Recognition, 17-22 June 2006, New York, USA.
We present a novel system for generic object class detection.
In contrast to most existing systems which focus on
a single viewpoint or aspect, our approach can detect object
instances from arbitrary viewpoints. This is achieved
by combining the Implicit Shape Model for object class detection
proposed by Leibe and Schiele with the multi-view
specific object recognition system of Ferrari et al.
After learning single-view codebooks, these are interconnected
by so-called activation links, obtained through
multi-view region tracks across different training views of
individual object instances. During recognition, these integrated
codebooks work together to determine the location
and pose of the object. Experimental results demonstrate
the viability of the approach and compare it to a bank of
independent single-view detectors.
|EPrint Type:||Conference or Workshop Item (Poster)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Deposited By:||Alexander Thomas|
|Deposited On:||18 August 2006|