About: Tracking-Learning-Detection

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	This paper investigates long-term tracking of unknown objects in a video stream. The object is defined by its location and extent in a single frame. In every frame that follows, the task is to determine the object?s location and extent or indicate that the object is not present. We propose a novel tracking framework (TLD) 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 the detector?s errors and updates it to avoid these errors in the future. We study how to identify the detector?s errors and learn from them. We develop a novel learning method (P-N learning) which estimates the errors by a pair of ?experts?: 1) P-expert estimates missed detections, and 2) N-expert estimates false alarms. The learning process is modeled as a discrete dynamical system and the conditions under which the learning guarantees improvement are found. We describe our real-time implementation of the TLD framework and the P-N learning. We carry out an extensive quantitative evaluation which shows a significant improvement over state-of-the-art approaches. This paper investigates long-term tracking of unknown objects in a video stream. The object is defined by its location and extent in a single frame. In every frame that follows, the task is to determine the object?s location and extent or indicate that the object is not present. We propose a novel tracking framework (TLD) 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 the detector?s errors and updates it to avoid these errors in the future. We study how to identify the detector?s errors and learn from them. We develop a novel learning method (P-N learning) which estimates the errors by a pair of ?experts?: 1) P-expert estimates missed detections, and 2) N-expert estimates false alarms. The learning process is modeled as a discrete dynamical system and the conditions under which the learning guarantees improvement are found. We describe our real-time implementation of the TLD framework and the P-N learning. We carry out an extensive quantitative evaluation which shows a significant improvement over state-of-the-art approaches. (en)
Title	Tracking-Learning-Detection Tracking-Learning-Detection (en)
skos:prefLabel	Tracking-Learning-Detection Tracking-Learning-Detection (en)
skos:notation	RIV/68407700:21230/12:00200439!RIV13-MSM-21230___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(7E11036), P(GAP103/10/1585)
http://linked.open...iv/cisloPeriodika	7
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Matas, Jiří
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	174783
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/12:00200439
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	tracking; long-term tracking (en)
http://linked.open.../riv/klicoveSlovo	long-term tracking tracking
http://linked.open...odStatuVydavatele	US - Spojené státy americké
http://linked.open...ontrolniKodProRIV	[B279F9B2EE36]
http://linked.open...i/riv/nazevZdroje	IEEE Transactions on Pattern Analysis and Machine Intelligence
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Advanced predictors for object detection and tracking in video Dextrous Assembler Robot Working with embodied INtelligence
http://linked.open...UplatneniVysledku	2012
http://linked.open...v/svazekPeriodika	34
http://linked.open...iv/tvurceVysledku	Matas, Jiří Mikolajczyk, K. Kálal, Z.
http://linked.open...ain/vavai/riv/wos	000304138300012
issn	0162-8828
number of pages	14 (xsd:int)
http://bibframe.org/vocab/doi	10.1109/TPAMI.2011.239
http://localhost/t...ganizacniJednotka	21230

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