Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optical Flow-based 3D Human Motion Estimation from Monocular Video   We present a generative method to estimate 3D human motion and body shape
from monocular video. Under the assumption that starting from an initial pose
optical flow constrains subsequent human motion, we exploit flow to find
temporally coherent human poses of a motion sequence. We estimate human motion
by minimizing the difference between computed flow fields and the output of an
artificial flow renderer. A single initialization step is required to estimate
motion over multiple frames. Several regularization functions enhance
robustness over time. Our test scenarios demonstrate that optical flow
effectively regularizes the under-constrained problem of human shape and motion
estimation from monocular video.

22
The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th