org.bytedeco.javacpp

Class opencv_tracking.MultiTrackerTLD

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.opencv_tracking.MultiTracker_Alt

org.bytedeco.javacpp.opencv_tracking.MultiTrackerTLD

All Implemented Interfaces:

AutoCloseable

Enclosing class:

opencv_tracking

@Namespace(value="cv")
public static class opencv_tracking.MultiTrackerTLD
extends opencv_tracking.MultiTracker_Alt

\brief 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 \cite TLD .

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

\sa Tracker, MultiTracker, TrackerTLD

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.Pointer.CustomDeallocator, org.bytedeco.javacpp.Pointer.Deallocator, org.bytedeco.javacpp.Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
MultiTrackerTLD() Default native constructor.
MultiTrackerTLD(long size) Native array allocator.
MultiTrackerTLD(org.bytedeco.javacpp.Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
opencv_tracking.MultiTrackerTLD	position(long position)
boolean	update_opt(opencv_core.GpuMat image)
boolean	update_opt(opencv_core.Mat image) \brief 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.
boolean	update_opt(opencv_core.UMat image)

Methods inherited from class org.bytedeco.javacpp.opencv_tracking.MultiTracker_Alt

addTarget, addTarget, addTarget, boundingBoxes, boundingBoxes, colors, colors, targetNum, targetNum, trackers, trackers, update, update, update

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

MultiTrackerTLD

public MultiTrackerTLD()

Default native constructor.

MultiTrackerTLD

public MultiTrackerTLD(long size)

Native array allocator. Access with Pointer.position(long).

MultiTrackerTLD

public MultiTrackerTLD(org.bytedeco.javacpp.Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

Method Detail

position

public opencv_tracking.MultiTrackerTLD position(long position)

Overrides:

position in class opencv_tracking.MultiTracker_Alt

update_opt

@Cast(value="bool")
public boolean update_opt(@ByVal
                                              opencv_core.Mat image)

\brief 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)

update_opt

@Cast(value="bool")
public boolean update_opt(@ByVal
                                              opencv_core.UMat image)

update_opt

@Cast(value="bool")
public boolean update_opt(@ByVal
                                              opencv_core.GpuMat image)