| Conference |
| Type of Publication |
| Motion-based Segmentation and Contour-based Classification
of Video Objects |
| Title |
|
Markus Beier
|
| Authors |
| Proc. ACM Multimedia 2001, pp.
41-50, Ottawa, Ontario, Canada, September 2001 |
| Published in |
| The segmentation of objects in video
sequences constitutes a prerequisite for numerous applications
ranging from computer vision tasks to second-generation video
coding.We propose an approach for segmenting video objects based
on motion cues. To estimate motion we employ the 3D structure
tensor, an operator that provides reliable results by integrating
information from a number of consecutive video frames. We present
a new hierarchical algorithm, embedding the structure tensor into
a multiresolution framework to allow the estimation of large
velocities.The motion estimates are included as an external force
into a geodesic active contour model, thus stopping the evolving
curve at the moving object's boundary. A level set-based
implementation allows the simultaneous segmentation of several
objects.As an application based on our object segmentation
approach we provide a video object classification system.
Curvature features of the object contour are matched by means of
a curvature scale space technique to a database containing
preprocessed views of prototypical objects.We provide encouraging
experimental results calculated on synthetic and real-world video
sequences to demonstrate the performance of our
algorithms. |
| Abstract |
|
| Projects |
|
motion segmentation
object classification
curvature scale space
structure tensor
|
| Keywords |
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