Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Ollivier-Ricci Curvature For Head Pose Estimation From a Single Image   Head pose estimation is a crucial challenge for many real-world applications,
such as attention and human behavior analysis. This paper aims to estimate head
pose from a single image by applying notions of network curvature. In the real
world, many complex networks have groups of nodes that are well connected to
each other with significant functional roles. Similarly, the interactions of
facial landmarks can be represented as complex dynamic systems modeled by
weighted graphs. The functionalities of such systems are therefore
intrinsically linked to the topology and geometry of the underlying graph. In
this work, using the geometric notion of Ollivier-Ricci curvature (ORC) on
weighted graphs as input to the XGBoost regression model, we show that the
intrinsic geometric basis of ORC offers a natural approach to discovering
underlying common structure within a pool of poses. Experiments on the BIWI,
AFLW2000 and Pointing'04 datasets show that the ORC_XGB method performs well
compared to state-of-the-art methods, both landmark-based and image-only.

15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn