Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Periocular Recognition Using CNN Features Off-the-Shelf   Periocular refers to the region around the eye, including sclera, eyelids,
lashes, brows and skin. With a surprisingly high discrimination ability, it is
the ocular modality requiring the least constrained acquisition. Here, we apply
existing pre-trained architectures, proposed in the context of the ImageNet
Large Scale Visual Recognition Challenge, to the task of periocular
recognition. These have proven to be very successful for many other computer
vision tasks apart from the detection and classification tasks for which they
were designed. Experiments are done with a database of periocular images
captured with a digital camera. We demonstrate that these off-the-shelf CNN
features can effectively recognize individuals based on periocular images,
despite being trained to classify generic objects. Compared against reference
periocular features, they show an EER reduction of up to ~40%, with the fusion
of CNN and traditional features providing additional improvements.

20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
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The categories of this paper are: eess
29
The categories of this paper are: funct-an