[−][src]Trait opencv::tracking::MultiTrackerTLDTrait

pub trait MultiTrackerTLDTrait: MultiTracker_AltTrait {
    fn as_raw_MultiTrackerTLD(&self) -> *const c_void;

    fn as_raw_mut_MultiTrackerTLD(&mut self) -> *mut c_void;

    fn update_opt(&mut self, image: &dyn ToInputArray) -> Result<bool> { ... }
}

Multi Object %Tracker for TLD.

TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into tracking, learning and detection.

The tracker follows the object from frame to frame. The detector localizes all appearances that have been observed so far and corrects the tracker if necessary. The learning estimates detector's errors and updates it to avoid these errors in the future. The implementation is based on TLD .

The Median Flow algorithm (see cv::TrackerMedianFlow) was chosen as a tracking component in this implementation, following authors. The tracker is supposed to be able to handle rapid motions, partial occlusions, object absence etc.

See also

Tracker, MultiTracker, TrackerTLD

Required methods

fn as_raw_MultiTrackerTLD(&self) -> *const c_void

fn as_raw_mut_MultiTrackerTLD(&mut self) -> *mut c_void

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Provided methods

fn update_opt(&mut self, image: &dyn ToInputArray) -> Result<bool>

Update all trackers from the tracking-list, find a new most likely bounding boxes for the targets by optimized update method using some techniques to speedup calculations specifically for MO TLD. The only limitation is that all target bounding boxes should have approximately same aspect ratios. Speed boost is around 20%

Parameters

  • image: The current frame.

Returns

True means that all targets were located and false means that tracker couldn't locate one of the targets in current frame. Note, that latter does not imply that tracker has failed, maybe target is indeed missing from the frame (say, out of sight)

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Implementors

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