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Davis King 2014-02-19 22:51:18 -05:00
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88
docs/docs/ml.xml
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@ -101,6 +101,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>structural_sequence_labeling_trainer</item>
<item>structural_sequence_segmentation_trainer</item>
<item>structural_assignment_trainer</item>
<item>structural_track_association_trainer</item>
<item>structural_graph_labeling_trainer</item>
<item>svm_rank_trainer</item>
</section>
@ -149,6 +150,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>cross_validate_sequence_labeler</item>
<item>cross_validate_sequence_segmenter</item>
<item>cross_validate_assignment_trainer</item>
<item>cross_validate_track_association_trainer</item>
<item>cross_validate_graph_labeling_trainer</item>
<item>cross_validate_ranking_trainer</item>
<item>test_binary_decision_function</item>
@ -158,6 +160,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>test_sequence_labeler</item>
<item>test_sequence_segmenter</item>
<item>test_assignment_function</item>
<item>test_track_association_function</item>
<item>test_graph_labeling_function</item>
<item>test_ranking_function</item>
<item>average_precision</item>
@ -208,6 +211,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>sequence_labeler</item>
<item>sequence_segmenter</item>
<item>assignment_function</item>
<item>track_association_function</item>
<item>graph_labeler</item>
</section>
@ -231,6 +235,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>is_sequence_segmentation_problem</item>
<item>is_graph_labeling_problem</item>
<item>is_assignment_problem</item>
<item>is_track_association_problem</item>
<item>is_forced_assignment_problem</item>
<item>approximate_distance_function</item>
<item>is_learning_problem</item>
@ -1534,6 +1539,36 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>track_association_function</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/track_association_function_abstract.h</spec_file>
<description>
This object is a tool that helps you implement an object tracker. So for
example, if you wanted to track people moving around in a video then this
object can help. In particular, imagine you have a tool for detecting the
positions of each person in an image. Then you can run this person
detector on the video and at each time step, i.e. at each frame, you get a
set of person detections. However, that by itself doesn't tell you how
many people there are in the video and where they are moving to and from.
To get that information you need to figure out which detections match each
other from frame to frame. This is where the track_association_function
comes in. It performs the detection to track association. It will also do
some of the track management tasks like creating a new track when a
detection doesn't match any of the existing tracks.
<p>
Internally, this object is implemented using the
<a href="#assignment_function">assignment_function</a> object.
In fact, it's really just a thin wrapper around assignment_function and
exists just to provide a more convenient interface to users doing detection
to track association.
</p>
</description>
</component>
<!-- ************************************************************************* -->
<component>
@ -1825,6 +1860,19 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>is_track_association_problem</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/svm_abstract.h</spec_file>
<description>
This function takes a set of training data for a track association learning problem
and reports back if it could possibly be a well formed track association problem.
</description>
</component>
<!-- ************************************************************************* -->
<component>
@ -2476,6 +2524,19 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>cross_validate_track_association_trainer</name>
<file>dlib/svm_threaded.h</file>
<spec_file link="true">dlib/svm/cross_validate_track_association_trainer_abstract.h</spec_file>
<description>
Performs k-fold cross validation on a user supplied track association trainer object such
as the <a href="#structural_track_association_trainer">structural_track_association_trainer</a>
and returns the fraction of detections which were correctly associated to their tracks.
</description>
</component>
<!-- ************************************************************************* -->
<component>
@ -2560,6 +2621,19 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>test_track_association_function</name>
<file>dlib/svm_threaded.h</file>
<spec_file link="true">dlib/svm/cross_validate_track_association_trainer_abstract.h</spec_file>
<description>
Tests a <a href="#track_association_function">track_association_function</a> on a set of data
and returns the fraction of detections which were correctly associated to their tracks.
</description>
</component>
<!-- ************************************************************************* -->
<component>
@ -2939,6 +3013,20 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>structural_track_association_trainer</name>
<file>dlib/svm_threaded.h</file>
<spec_file link="true">dlib/svm/structural_track_association_trainer_abstract.h</spec_file>
<description>
This object is a tool for learning to solve a track association problem. That
is, it takes in a set of training data and outputs a
<a href="#track_association_function">track_association_function</a>
you can use to do detection to track association.
</description>
</component>
<!-- ************************************************************************* -->
<component>

7
docs/docs/term_index.xml
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@ -79,18 +79,25 @@
<term file="ml.html" name="is_forced_assignment_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_assignment_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_track_association_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_graph_labeling_problem" include="dlib/svm_threaded.h"/>
<term file="dlib/svm/structural_svm_graph_labeling_problem_abstract.h.html" name="sizes_match" include="dlib/svm_threaded.h"/>
<term file="dlib/svm/structural_svm_graph_labeling_problem_abstract.h.html" name="all_values_are_nonnegative" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="assignment_function" include="dlib/svm.h"/>
<term file="ml.html" name="track_association_function" include="dlib/svm.h"/>
<term file="dlib/svm/track_association_function_abstract.h.html" name="feature_extractor_track_association"
include="dlib/svm.h"/>
<term file="ml.html" name="graph_labeler" include="dlib/graph_cuts.h"/>
<term file="ml.html" name="test_assignment_function" include="dlib/svm.h"/>
<term file="ml.html" name="test_track_association_function" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="test_graph_labeling_function" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="cross_validate_assignment_trainer" include="dlib/svm.h"/>
<term file="ml.html" name="cross_validate_track_association_trainer" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="cross_validate_graph_labeling_trainer" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="structural_svm_assignment_problem" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="structural_svm_graph_labeling_problem" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="structural_assignment_trainer" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="structural_track_association_trainer" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="structural_graph_labeling_trainer" include="dlib/svm_threaded.h"/>
<term file="dlib/optimization/optimization_solve_qp2_using_smo_abstract.h.html" name="invalid_nu_error" include="dlib/optimization.h"/>