Internship: Detecting lightning strikes in high-speed videos

Informatik Ingenieurwissenschaften

The Aragats Space Environmental Center (ASEC) studies the first stages of the lightning initiation and develops models of electron acceleration in the thunderclouds. Multiple detectors located close to the summit of Mt. Aragats record the electric field and the inciting fluxes of neutral and charged particles at very high rates. Additionally, multiple high-speed visible-light cameras continuously monitor the sky. Due to limitations of the available data storage, it is impossible to record the complete video stream. Instead an intelligent data acquisition software is required to identify frames with lightning events and store only these ones.

During the internship the student will analyze methods to detect lightnings in the video stream and develop a real-time implementation of these methods. These methods should be robust enough to handle also low quality videos acquired with the low exposure times and night scenes. As the required frame rates exceeds 1000 fps, an efficient parallel implementation for the modern GPU accelerators is needed. Additional speed-up can be achieved by correlating the data from other detectors with lower data rates to pre-filter time intervals when the lightnings are likely to happen. The project is carried out in collaboration between KIT and ASEC in Armenia.

Weitere Informationen

Unternehmen: Helmholtz Gemeinschaft
Standort: Karlsruhe, Baden-Württemberg, Deutschland
Anstellungsart: Praktikum
Vertiegungsgebiet: Forschung und Entwicklung
Ansprechpartner/in: Fachliche Auskünfte erteilt Ihnen gerne Dr. Suren Chilingaryan, IPE, +49 721 / 608 26579, (suren.chilingaryan@kit edu)

Bitte senden Sie Ihre Bewerbung online unter Angabe der Stellenausschreibungsnummer IPE 12-16 an Frau Berger, Berufliche Ausbildung, Telefon 0721 608-25184.
Bei entsprechender Eignung werden schwerbehinderte Bewerber/innen bevorzugt berücksichtigt.
Anforderungen: Good background in computer vision, strong knowledge of C/C++ programming. Prior experience in parallel programming using CUDA or OpenCL is a plus.
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