Selection of Scale-Invariant Parts for Object Class Recognition

In this paper, we proposed a novel kind of evaluation corpus, which we called an Integrated Corpus for the Evaluation of Named Entity Recognition and Object Consolidation. It can

[10] M. Lenz, Emotion related structures in large image databases, in: Proceedings of the ACM International Conference on Image and Video Retrieval, ACM, 2010, pp.. Hanbury,

While our previous method [12] showed promising results, it came with sev- eral limitations: (i) the α-tree has to be computed on the full video sequence before any further

Figure 1 and Figure 2 respectively show the plot of difference, without and with consolidation, in the number of SIFT key points (left vertical axis) and

As for the comparison in a global context, the learning database is now composed for all the 100 objects of the 72 views without alteration and the recognition rate is computed

sift descriptors are the best ones to compute Inter similarities as they are able to reject object from other category whereas koen descriptors are the best ones to compute

Our contribution suggests performing class pairwise feature selection in or- der to find the most efficient features in discriminating be- tween a given comparison of 2 instruments..

Next, we use the classi- cal forward/backward selection method combined with logistic regression [21] since other feature selection methods, such as random forest, do not provide