Public Member Functions

projection_state< observation_type > Class Template Reference

#include <projection_state.h>

Inheritance diagram for projection_state< observation_type >:
skeleton_state< observation_type > state< observation_type >

List of all members.

Public Member Functions

 projection_state (const options &opts, const calibration &_calib, const bool _for_show=true)
double predict (const observation_type &observation, const double variance_scale=1.0)
projection_state & operator= (projection_state &new_state)
bool load (const std::string filename)
bool load (std::ifstream &file)

Detailed Description

template<class observation_type>
class projection_state< observation_type >

An implementation of the projected prior. If you use this class we recommend citing 

 @inproceedings{spatial_priors:hauberg_et_al10,
  title = {{Gaussian-like Spatial Priors for Articulated Tracking}},
  author = {S{\o}ren Hauberg and Stefan Sommer and Kim Steenstrup Pedersen},
  booktitle = {ECCV},
  year = "2010",
  pages = "425--437",
  editor = {K. Daniilidis and P. Maragos and N. Paragios},
  publisher = {Springer},
  series = {LNCS},
  volume = {6311}
 }

Constructor & Destructor Documentation

template<class observation_type>
projection_state< observation_type >::projection_state ( const options &  opts,
const calibration &  _calib,
const bool  _for_show = true 
) [inline]

Member Function Documentation

template<class observation_type>
bool projection_state< observation_type >::load ( const std::string  filename  )  [inline]

Load pose parameters from a file.

Parameters:
[in] filename The name of the file containing the pose paramters.
Returns:
TRUE on succes.

Reimplemented from skeleton_state< observation_type >.

template<class observation_type>
bool projection_state< observation_type >::load ( std::ifstream &  file  )  [inline]

Load pose parameters from a stream. This is useful for batch loads.

Parameters:
[in] file A stream representing the open file.
Returns:
TRUE on succes.

Reimplemented from skeleton_state< observation_type >.

template<class observation_type>
projection_state& projection_state< observation_type >::operator= ( projection_state< observation_type > &  new_state  )  [inline]
template<class observation_type>
double projection_state< observation_type >::predict ( const observation_type &  observation,
const double  variance_scale = 1.0 
) [inline, virtual]

The importance distribution of the tracker.

Parameters:
[in] observation The current observation.
[in] variance_scale A scale factor for the default variance. This is used for annealed filters.
Returns:
The correction factor for the importance distribution (most often 1).

Implements state< observation_type >.

The documentation for this class was generated from the following file:
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