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some bugfixes & improvements in openfabmap code, docs and samples by Arren Glover

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This commit is contained in:
Vadim Pisarevsky
2012-09-23 20:57:34 +04:00
parent b7b32e74a5
commit 427ce1247a
3 changed files with 27 additions and 11 deletions
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2
modules/contrib/doc/openfabmap.rst
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@@ -3,7 +3,7 @@ openFABMAP
.. highlight:: cpp
The openFABMAP package has been integrated into OpenCV from the openFABMAP <http://code.google.com/p/openfabmap/> project. OpenFABMAP is an open and modifiable code-source which implements the Fast Appearance-based Mapping algorithm (FAB-MAP) developed by Mark Cummins and Paul Newman. The algorithms used in openFABMAP were developed using only the relevant FAB-MAP publications.
The openFABMAP package has been integrated into OpenCV from the openFABMAP <http://code.google.com/p/openfabmap/> project [ICRA2011]_. OpenFABMAP is an open and modifiable code-source which implements the Fast Appearance-based Mapping algorithm (FAB-MAP) developed by Mark Cummins and Paul Newman. The algorithms used in openFABMAP were developed using only the relevant FAB-MAP publications.
FAB-MAP is an approach to appearance-based place recognition. FAB-MAP compares images of locations that have been visited and determines the probability of re-visiting a location, as well as providing a measure of the probability of being at a new, previously unvisited location. Camera images form the sole input to the system, from which visual bag-of-words models are formed through the extraction of appearance-based (e.g. SURF) features.

15
modules/contrib/src/openfabmap.cpp
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@@ -202,14 +202,13 @@ void FabMap::compare(const vector<Mat>& queryImgDescriptors,
void FabMap::compare(const vector<Mat>& queryImgDescriptors,
const vector<Mat>& _testImgDescriptors,
vector<IMatch>& matches, const Mat& /*mask*/) {
if (_testImgDescriptors[0].data != this->testImgDescriptors[0].data) {
CV_Assert(!(flags & MOTION_MODEL));
for (size_t i = 0; i < _testImgDescriptors.size(); i++) {
CV_Assert(!_testImgDescriptors[i].empty());
CV_Assert(_testImgDescriptors[i].rows == 1);
CV_Assert(_testImgDescriptors[i].cols == clTree.cols);
CV_Assert(_testImgDescriptors[i].type() == CV_32F);
}
CV_Assert(!(flags & MOTION_MODEL));
for (size_t i = 0; i < _testImgDescriptors.size(); i++) {
CV_Assert(!_testImgDescriptors[i].empty());
CV_Assert(_testImgDescriptors[i].rows == 1);
CV_Assert(_testImgDescriptors[i].cols == clTree.cols);
CV_Assert(_testImgDescriptors[i].type() == CV_32F);
}
for (size_t i = 0; i < queryImgDescriptors.size(); i++) {