|
|
Online interest point detector
Přibyl, Jakub ; Rajnoha, Martin (referee) ; Mašek, Jan (advisor)
This thesis focuses on online learning detector for long-term tracking of object in video sequence. The object is defined by a bounding box. The text describes different parts of the detector: object tracking, object detection and online learning detector. The main contribution of this work is creating extension of the OpenTLD program for parallel detection and tracking of multiple objects. The parallelization is then compared on two practical examples and the processor's impact on detection is compared. The best results were achieved with parallelization, where all objects were detected. The most accurate detection was in the case of sufficiently learned objects with the smallest shape change.
|
|
|
Image Tracking in Video Sequences
Pavlík, Vít ; Musil, Petr (referee) ; Zemčík, Pavel (advisor)
Master's thesis addresses the long-term image tracking in video sequences. The project was intended to demonstrate the techniques that are needed for handling the long-term tracking. It primarily describes the techniques which application leads to construction of adaptive tracking system which is able to deal with the change of appearance of the object and unstable character of the surrounding environement appropriately.
|
|
|
Learning Detectors by Tracking
Buchtela, Radim ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
This thesis is devoted to learn detectors by object tracking in video sequence. In this thesis, we discuss methods for object tracking, object detection and online learning and possibilities of their using in sophisticated techniques, which combine object tracking and online learning detectors.
|
|
|
Online interest point detector
Přibyl, Jakub ; Rajnoha, Martin (referee) ; Mašek, Jan (advisor)
This thesis focuses on online learning detector for long-term tracking of object in video sequence. The object is defined by a bounding box. The text describes different parts of the detector: object tracking, object detection and online learning detector. The main contribution of this work is creating extension of the OpenTLD program for parallel detection and tracking of multiple objects. The parallelization is then compared on two practical examples and the processor's impact on detection is compared. The best results were achieved with parallelization, where all objects were detected. The most accurate detection was in the case of sufficiently learned objects with the smallest shape change.
|
|
|
Image Tracking in Video Sequences
Pavlík, Vít ; Musil, Petr (referee) ; Zemčík, Pavel (advisor)
Master's thesis addresses the long-term image tracking in video sequences. The project was intended to demonstrate the techniques that are needed for handling the long-term tracking. It primarily describes the techniques which application leads to construction of adaptive tracking system which is able to deal with the change of appearance of the object and unstable character of the surrounding environement appropriately.
|
|
|
Learning Detectors by Tracking
Buchtela, Radim ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
This thesis is devoted to learn detectors by object tracking in video sequence. In this thesis, we discuss methods for object tracking, object detection and online learning and possibilities of their using in sophisticated techniques, which combine object tracking and online learning detectors.
|
guest ::
