Ideas for Feature-basedTracking Improvements : Différence entre versions

De Transport
 
(3 révisions intermédiaires par le même utilisateur non affichées)
Ligne 1 : Ligne 1 :
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* feature tracking
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** keep looking for optical flow matches for lost features (then interpolate linearly if found again)
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** keep stationary features who have moved enough in the past (remove stationary part if they do not move again)
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** detect keypoints continuously over the whole image to check that a feature trajectory would have some level of continuous detection
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** run shadow detection and remove features mostly detected as shadow over time
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* avoid over grouping
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stats on motion model: acceleration, speed for normal and overgrouped
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* Classify features (based on speed, image patch, image foreground) and connect accordingly
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compute gait/kinematic parameters and connect accordingly
 
* Add and modulate the similarity constraints
 
* Add and modulate the similarity constraints
 
constant distance over time
 
constant distance over time

Version actuelle en date du 6 juin 2014 à 12:19

  • feature tracking
    • keep looking for optical flow matches for lost features (then interpolate linearly if found again)
    • keep stationary features who have moved enough in the past (remove stationary part if they do not move again)
    • detect keypoints continuously over the whole image to check that a feature trajectory would have some level of continuous detection
    • run shadow detection and remove features mostly detected as shadow over time
  • avoid over grouping

stats on motion model: acceleration, speed for normal and overgrouped

  • Classify features (based on speed, image patch, image foreground) and connect accordingly

compute gait/kinematic parameters and connect accordingly

  • Add and modulate the similarity constraints

constant distance over time similar velocity angle robust: percentage of time that the condition must be met

  • Extend the graph with weights instead of 0/1 (edge or not)