|View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance|
|Zhaoxiang Zhang; Min Li; Kaiqi Huang; Tieniu Tan
|Conference Name||The Eighth International Workshop on Visual Surveillance
|Source Publication||IEEE Conference on Computer Vision & Pattern Recognition 2008
|Conference Date||17th October 2008
|Abstract||We address the problem of view independent object classification.
Our aim is to classify moving objects of traf-
fic scene surveillance videos into pedestrians, bicycles and
vehicles. However, this problem is very challenging due
to large object appearance variance, low resolution videos
and limited object size. Especially, perspective distortion
of surveillance cameras makes most 2D object features like
size and speed related to view angles and not suitable for
object classification. In this paper, we adopt the common
constraint that most objects of interest in traffic scenes are
moving on the ground plane. Firstly, we realize the ground
plane rectification based on appearance and motion information
of moving objects, which can be applied for normalization
of 2D object features. An online learning framework
is then described to achieve automatic object classification
based on rectified 2D object features. Experimental results
demonstrate the effectiveness, efficiency and robustness of
the proposed method.|
|Keyword||Traffic Scene Surveillance
Automated Ground Plane Rectification
View Independent Object Classification
Online Learning Framework
|Corresponding Author||Zhaoxiang Zhang|
Zhaoxiang Zhang,Min Li,Kaiqi Huang,et al. View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance[C],2008:1-9.
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