initDistributionFast

PURPOSE ^

INITDISTRIBUTIONFAST.m initializes the depth distribution of the DS-KCF tracker

SYNOPSIS ^

function [targetDepth,targetStd,LabelReg,regionIndex,Centers,LUT] = initDistributionFast(bbIn, depth16Bit,noData)

DESCRIPTION ^

 INITDISTRIBUTIONFAST.m initializes the depth distribution of the DS-KCF tracker

   INITDISTRIBUTIONFAST function initializes the depth distribution of the
   tracked object at the beginning of the sequence. In particular, the
   fast depth segmentation algorithm described in [1] is used

   INPUT:
  -bbIn bounding box containing the tracked object. Format of the bounding
  box is [topLeftX, topLeftY, bottomRightX, bottomRightY] read as
  [rowIndexTopLeft, columnIndexTopLeft,rowIndexBottomRight,
  columnIndexBottomRight]
  -depth16Bit depth data in mm
  -noData binary mask containing information about missing depth pixels

   OUTPUT
  -targetDepth mean depth value of the cluster containing the target
  -targetStd standard deviation of the cluster containing the target
  -LabelReg connected component with cluster labels
  -regionIndex label of the target's cluster (or the closest object to the
  camera)
  -Centers depth value corresponding to the identified connected
  components
  -LUT look-up-table containing the connected component labels and the
  corresponding mean depth value

  See also ROIFROMBB, FASTDEPTHSEGMENTATIONDSKCF_INITFRAME, WRAPPERDSKCF

  [1] S. Hannuna, M. Camplani, J. Hall, M. Mirmehdi, D. Damen, T.
  Burghardt, A.Paiement, L. Tao, DS-KCF: A real-time tracker for RGB-D
  data, Journal of Real-Time Image Processing


  University of Bristol
  Massimo Camplani and Sion Hannuna

  massimo.camplani@bristol.ac.uk
  hannuna@compsci.bristol.ac.uk

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [targetDepth,targetStd,LabelReg,regionIndex,Centers,LUT] = initDistributionFast(bbIn, depth16Bit,noData)
0002 % INITDISTRIBUTIONFAST.m initializes the depth distribution of the DS-KCF tracker
0003 %
0004 %   INITDISTRIBUTIONFAST function initializes the depth distribution of the
0005 %   tracked object at the beginning of the sequence. In particular, the
0006 %   fast depth segmentation algorithm described in [1] is used
0007 %
0008 %   INPUT:
0009 %  -bbIn bounding box containing the tracked object. Format of the bounding
0010 %  box is [topLeftX, topLeftY, bottomRightX, bottomRightY] read as
0011 %  [rowIndexTopLeft, columnIndexTopLeft,rowIndexBottomRight,
0012 %  columnIndexBottomRight]
0013 %  -depth16Bit depth data in mm
0014 %  -noData binary mask containing information about missing depth pixels
0015 %
0016 %   OUTPUT
0017 %  -targetDepth mean depth value of the cluster containing the target
0018 %  -targetStd standard deviation of the cluster containing the target
0019 %  -LabelReg connected component with cluster labels
0020 %  -regionIndex label of the target's cluster (or the closest object to the
0021 %  camera)
0022 %  -Centers depth value corresponding to the identified connected
0023 %  components
0024 %  -LUT look-up-table containing the connected component labels and the
0025 %  corresponding mean depth value
0026 %
0027 %  See also ROIFROMBB, FASTDEPTHSEGMENTATIONDSKCF_INITFRAME, WRAPPERDSKCF
0028 %
0029 %  [1] S. Hannuna, M. Camplani, J. Hall, M. Mirmehdi, D. Damen, T.
0030 %  Burghardt, A.Paiement, L. Tao, DS-KCF: A real-time tracker for RGB-D
0031 %  data, Journal of Real-Time Image Processing
0032 %
0033 %
0034 %  University of Bristol
0035 %  Massimo Camplani and Sion Hannuna
0036 %
0037 %  massimo.camplani@bristol.ac.uk
0038 %  hannuna@compsci.bristol.ac.uk
0039 
0040 %extract the target roi, from the depth and the nodata mask
0041 front_depth=roiFromBB(depth16Bit,bbIn);
0042 depthNoData=roiFromBB(noData,bbIn);
0043 
0044 [LabelReg,Centers,LUT]=fastDepthSegmentationDSKCF_initFrameV2(front_depth,3,depthNoData,1,50,[-1 -1 -1],1);
0045 
0046 %for the initialization the object belong to the cluster with the smaller
0047 %depth (see [1] for more details)
0048 [targetDepth,regionIndex]=min(Centers);
0049 %extract all the depth value belonging to that cluster
0050 depthVector=double(front_depth(LabelReg==regionIndex));
0051 %then calculate the standard deviation
0052 targetStd=std(depthVector);
0053 
0054 end
0055

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