Tracking

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

const string cv::datasets::sectionNames[]

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" }

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