Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Object Recognition by Using Multi-level Feature Point Extraction   In this paper, we present a novel approach for object recognition in
real-time by employing multilevel feature analysis and demonstrate the
practicality of adapting feature extraction into a Naive Bayesian
classification framework that enables simple, efficient, and robust
performance. We also show the proposed method scales well as the number of
level-classes grows. To effectively understand the patches surrounding a
keypoint, the trained classifier uses hundreds of simple binary features and
models class posterior probabilities. In addition, the classification process
is computationally cheap under the assumed independence between arbitrary sets
of features. Even though for some particular scenarios, this assumption can be
invalid. We demonstrate that the efficient classifier nevertheless performs
remarkably well on image datasets with a large variation in the illumination
environment and image capture perspectives. The experiment results show
consistent accuracy can be achieved on many challenging dataset while offer
interactive speed for large resolution images. The method demonstrates
promising results that outperform the state-of-the-art methods on pattern
recognition.

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The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
21
The categories of this paper are: adap-org
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol