A Cheat Sheet For Multi-Object Tracking
Multiple Object Tracking(MOT)
MOT takes a single continuous video and splits it into discrete frames at a specific frame rate(fps) to output
- Detection: what objects are present in each frame
- Localization: where objects are in each frame
- Association: whether objects in different frames belong to the same or different objects
Typical Applications of MOT
Multi-object tracking(MOT) has its application in
- Video surveillance for traffic control, digital forensics
- Gesture recognition
- Augmented Reality
- Self-driving vehicles
Challenges with MOT
- Accurately detect the objects of interest in the frame with high confidence. Issues with accurate object detection are failing to detect an object of interest, assigning a wrong class label to a detected object, or incorrectly localizing an identified object.
- ID Switching occurs when two similar objects overlap or blend, causing the identity switching; hence, keeping track of the object id is difficult.
- Background distortion: Busy background makes it difficult to detect small objects during object detection
- Occlusion: occurs when something you want to see is hidden or occluded by another object.
- Multiple Spatial Spaces, Deformation, or Object rotation
- Image illumination
- Visual streaking or smearing captured on camera due to motion blur
Characteristics of a Multi-object tracker(MOT)
A good multi-object tracker(MOT)
- Tracks object by identifying the correct number of trackers at the precise locations in each frame.
- Identify objects by tracking individual objects consistently over a long period,
- Track objects despite occlusion, illumination changes, background, motion blur, etc.
- Detect and Track objects fast