diplomsko delo
Tomaž Bevk (Avtor), Aleš Leonardis (Mentor)

Povzetek

Sledenje s sprotnim izbiranjem značilnic za sočasno lokalizacijo in kartografiranje z eno samo kamero

Ključne besede

avtonomni mobilni roboti;boosting;računalniški vid;sledenje;strojno učenje;računalništvo;univerzitetni študij;diplomske naloge;

Podatki

Jezik: Slovenski jezik
Leto izida:
Tipologija: 2.11 - Diplomsko delo
Organizacija: UL FRI - Fakulteta za računalništvo in informatiko
Založnik: [T. Bevk]
UDK: 004.9(043.2)
COBISS: 6738516 Povezava se bo odprla v novem oknu
Št. ogledov: 1149
Št. prenosov: 297
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarni naslov: [Tracking with online selection of features for simultaneous localization and mapping using a single camera]
Sekundarni povzetek: Development of algorithms for autonomous mobile robots is one of the main subjects that concerns the field of computer vision. One of the approaches introduces a concept called simultaneous localization and mapping (SLAM), by which a mobile robot can build a map of an environment, and at the same time, use this map to compute its own location. The robot can gather the information about the environment with the use of many different sensors. In our work we focus on systems that use a single camera for this purpose. One of the tasks that has to be tackled by a SLAM system, is tracking of objects that are present in the environment. Because we expect the robot to be constantly moving, we can presume that, from the robot's point of view, the appearance of the tracked objects will change. In order to resolve this problem we implemented a tracker that is capable of adapting to the changing appearance of the tracked object. We achieved this by translating the problem of tracking into a classification problem and by using some of the methods provided by the field of machine learning. We integrated the obtained tracker into an allready existent application of SLAM, called MonoSLAM. Results of our tests showed that such combination performs better in some situations than does the basic MonoSLAM, although in other situations the very ability of adapting makes the system fail. In the concluding section we point out some possible improvements and give suggestions for further research.
Sekundarne ključne besede: autonomous mobile robots;boosting;computer vision;machine learning;tracking;computer science;diploma;
Vrsta datoteke: application/pdf
Vrsta dela (COBISS): Diplomsko delo
Komentar na gradivo: Univerza v Ljubljani, Fakulteta za računalništvo in informatiko
Strani: VIII, 75 str.
ID: 23809268