Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Using Interval Particle Filtering for Marker less 3D Human Motion
  Capture   In this paper we present a new approach for marker less human motion capture
from conventional camera feeds. The aim of our study is to recover 3D positions
of key points of the body that can serve for gait analysis. Our approach is
based on foreground segmentation, an articulated body model and particle
filters. In order to be generic and simple no restrictive dynamic modelling was
used. A new modified particle filtering algorithm was introduced. It is used
efficiently to search the model configuration space. This new algorithm which
we call Interval Particle Filtering reorganizes the configurations search space
in an optimal deterministic way and proved to be efficient in tracking natural
human movement. Results for human motion capture from a single camera are
presented and compared to results obtained from a marker based system. The
system proved to be able to track motion successfully even in partial
occlusions.

17
The categories of this paper are: q-fin
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org