- AutorIn
- Nikhilesh Vempati
- Titel
- Extraction of Key-Frames from an Unstable Video Feed
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:ch1-qucosa-229054
- Datum der Verteidigung
- 13.07.2017
- Abstract (EN)
- The APOLI project deals with Automated Power Line Inspection using Highly-automated Unmanned Aerial Systems. Beside the Real-time damage assessment by on-board high-resolution image data exploitation a postprocessing of the video data is necessary. This Master Thesis deals with the implementation of an Isolator Detector Framework and a Work ow in the Automotive Data and Time-triggered Framework(ADTF) that loads a video direct from a camera or from a storage and extracts the Key Frames which contain objects of interest. This is done by the implementation of an object detection system using C++ and the creation of ADTF Filters that perform the task of detection of the objects of interest and extract the Key Frames using a supervised learning platform. The use case is the extraction of frames from video samples that contain Images of Isolators from Power Transmission Lines.
- Freie Schlagwörter (DE)
- Objektdetektierung, SVM, Bildverarbeitung
- Freie Schlagwörter (EN)
- Object Detection, Key-Frame Extraction, ADTF, SVM
- Klassifikation (DDC)
- 004
- Normschlagwörter (GND)
- Informatik, Bildverarbeitung, Video
- GutachterIn
- Dr. Ariane Heller
- Prof. Dr. Wolfram Hardt
- BetreuerIn
- Dr. Ariane Heller
- Den akademischen Grad verleihende / prüfende Institution
- Technische Universität Chemnitz, Chemnitz
- URN Qucosa
- urn:nbn:de:bsz:ch1-qucosa-229054
- Veröffentlichungsdatum Qucosa
- 28.09.2017
- Dokumenttyp
- Masterarbeit / Staatsexamensarbeit
- Sprache des Dokumentes
- Englisch