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Extraction of Key-Frames from an Unstable Video Feed

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.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:20781
Date13 July 2017
CreatorsVempati, Nikhilesh
ContributorsHeller, Ariane, Hardt, Wolfram, Technische Universität Chemnitz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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