Discriminative, and Ensemble Learning on Multi-Modal Perceptual Fusion
Toward News Video Story Segmentation
Winston H.-M. Hsu and Shih-Fu Chang
ICME 2004 Reviews' comments :
>> Reviewer 1
Very good paper.
>> Reviewer 2
In this paper, the author describes a novel approach to news
videos segmentation. Author's segmentation method is based on
earlier work using a Maximum Entropy model.
The author proposed this new
and alternative approach based on
a discriminative model, ensemble learning as well as the
original idea of proposing a method that uses combination of
ME classifiers and the associated confidence scores in each
Author also compared results
of SVM-based, ME-based with pure
boosting approach, indicated in his experiment section showing
>> Reviewer 3
It is not a surprise that BST-BIN-35
did not perform
well as each classifier is based on single binary
feature i.e. they are too weak to be boosted, let
alone the cost of 35 training iterations.
Some description on the video
story types (a)-(i)
and the reason of the performance variation would
Fig. 2 is hard to read as there
are too many curves.