# Content-Based Video Retrieval in Historical Collections of the German Broadcasting Archive

## TL;DR

This paper presents an automatic video analysis and retrieval system designed for the German Broadcasting Archive's historical GDR television recordings, enabling efficient content-based search through various analysis algorithms.

## Contribution

It introduces a comprehensive system combining shot boundary detection, concept classification, person recognition, text recognition, and similarity search for historical video archives.

## Key findings

- System evaluated on 2,500 hours of recordings
- Achieved effective retrieval performance from technical and archival perspectives
- Demonstrated feasibility of automated analysis for large historical video collections

## Abstract

The German Broadcasting Archive (DRA) maintains the cultural heritage of radio and television broadcasts of the former German Democratic Republic (GDR). The uniqueness and importance of the video material stimulates a large scientific interest in the video content. In this paper, we present an automatic video analysis and retrieval system for searching in historical collections of GDR television recordings. It consists of video analysis algorithms for shot boundary detection, concept classification, person recognition, text recognition and similarity search. The performance of the system is evaluated from a technical and an archival perspective on 2,500 hours of GDR television recordings.