OpenCV  3.4.19
Open Source Computer Vision
Classes | Variables

Classes

class  cv::datasets::TRACK_alov
 
struct  cv::datasets::TRACK_alovObj
 
class  cv::datasets::TRACK_vot
 
struct  cv::datasets::TRACK_votObj
 

Variables

const string cv::datasets::sectionNames []
 
const int cv::datasets::sectionSizes [] = { 33, 15, 18, 20, 24, 22, 12, 15, 37, 23, 34, 22, 29, 10 }
 

Detailed Description

VOT 2015 Database

Implements loading dataset:

"VOT 2015 dataset comprises 60 short sequences showing various objects in challenging backgrounds. The sequences were chosen from a large pool of sequences including the ALOV dataset, OTB2 dataset, non-tracking datasets, Computer Vision Online, Professor Bob Fisher's Image Database, Videezy, Center for Research in Computer Vision, University of Central Florida, USA, NYU Center for Genomics and Systems Biology, Data Wrangling, Open Access Directory and Learning and Recognition in Vision Group, INRIA, France. The VOT sequence selection protocol was applied to obtain a representative set of challenging sequences.": http://box.vicos.si/vot/vot2015.zip

Usage:

  1. From link above download dataset file: vot2015.zip
  2. Unpack vot2015.zip into folder: VOT2015/
  3. To load data run:
    ./opencv/build/bin/example_datasets_track_vot -p=/home/user/path_to_unpacked_files/VOT2015/

Variable Documentation

◆ sectionNames

const string cv::datasets::sectionNames[]

#include <opencv2/datasets/track_alov.hpp>

Initial value:
= { "01-Light", "02-SurfaceCover", "03-Specularity", "04-Transparency", "05-Shape", "06-MotionSmoothness", "07-MotionCoherence",
"08-Clutter", "09-Confusion", "10-LowContrast", "11-Occlusion", "12-MovingCamera", "13-ZoomingCamera", "14-LongDuration" }

◆ sectionSizes

const int cv::datasets::sectionSizes[] = { 33, 15, 18, 20, 24, 22, 12, 15, 37, 23, 34, 22, 29, 10 }