| OpenCV 4.3.0 Open Source Computer Vision

Classes | Variables
Tracking
Framework for working with different datasets

## 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 }

`#include <opencv2/datasets/track_alov.hpp>`