t racking l earning d etection
DESCRIPTION
T racking L earning D etection. A Camera that Learns. Why is object tracking so important ?. vehicle detection. motion capture. r obot vision. scene analysis. hand recognition. surveillance. Outline. Why TLD?. - Traditional methods- Challenges to old ways. What is TLD intuitively?. - PowerPoint PPT PresentationTRANSCRIPT
TrackingLearningDetection
A Camera that Learns.
Why is object tracking so important ?
surveillance
hand recognitionscene analysisve
hicl
e de
tecti
on
robot vision
motion capture
Outline
- Framework - Key ideasWhat is TLD intuitively?
How does TLD work exactly?
Experiment Results
Why TLD?- Traditional methods - Challenges to old ways
- Tracking - Learning - Detection - TLD
Why TLD ?
Why TLD ?
Why TLD ?- Traditional method 1 :Tracking
Accumulate error.Fail if the object disappears.
Only need initialization.Appearance changing & Partial occlusions. (?)
Estimate motion over frames
Why TLD ?- Traditional method 2 :
DetectionOff-line
Learning
Do not fail if the object disappears.
Need off-line training.Appearance changing & Partial occlusions.
Scan every frame independently
Why TLD ?- Challenges to old ways• Not fail if the object disappears.
• Appearance changing.
• Partial occlusions.
Why TLD ?- Challenges to old ways• Not fail if the object disappears.
• Appearance changing.
• Partial occlusions.
TLD is an algorithm
that can solve all these tasks !
What is TLD intuitively?
What is TLD intuitively?- Framework
Tracking
DetectionOff-line
Learning
What is TLD intuitively?- Framework
Tracking Detection
On-lineLearning
Update
LocationTrajectoryfragment
Update
What is TLD intuitively?- Key ideas 1 : Learning
Track & detect
Track
Detect
Updatestraining examples
(add/delete)
Update detector
•Appearance changing.
What is TLD intuitively?- Key ideas 2 : Updating
True trajectory Tracking Detection
TLD
• Not fail if no object.
• Partial occlusions.
How does TLD work exactly?
How does TLD work exactly?- Framework
How does TLD work exactly?- Tracking
1.Reliable point selection:
Choose point 1
Discard point 2
- Use forward-backward selection to select 50% of the most reliable points.
- Forward-backward selection
How does TLD work exactly?- Tracking
2.Median-Flow tracker:
Tracks the reliable points between consecutive frames ,
and estimates displacement using median with confidence proportional to (1/scale of the median).
How does TLD work exactly?- Framework
How does TLD work exactly?- Detection
2bitBPfeatures
Scanningwindow
2bitBP features
Illuminationinvariance
How does TLD work exactly?- Detection
RandomForest
Posteriors
2bitBPfeatures
Scanningwindow
Random Forest
If the average posteriors is larger than 50%, consider it an object
How does TLD work exactly?- Detection
1-NN classifierConfidence =d-/(d-+d+)Random
ForestPosteriors
2bitBPfeatures
Scanningwindow
Feature space
How does TLD work exactly?- Framework
Pick the one with higher confidence score
How does TLD work exactly?- Learning
Feature space
How does TLD work exactly?- Learning
Track & detect
Track
Detect
Updatestraining examples
(add/delete)
Update detector
How does TLD work exactly?- Learning :
1
6
10
Appearance changingproblem solved!
9
How does TLD work exactly? - Recap : t=0
How does TLD work exactly? - Recap : t=1
Decide by confidence
score
How does TLD work exactly? - Recap : t=1
How does TLD work exactly? - Recap : t=2
Remove if false detect
Experiment Result
Experiment Result
Experiment Result
Experiment Result
Thank you