Content-based video retrieval in historical collections of the German Broadcasting Archive

Mühling, Markus; Meister, Manja; Korfhage, Nikolaus; Wehling, Jörg; Hörth, Angelika; Ewerth, Ralph; Freisleben, Bernd

doi:10.1007/s00799-018-0236-z

Cited by 25 publications

(7 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In a previous project that realized content-based video retrieval in historical GDR television data, a GDR specific lexicon of 100 classes (91 concepts and 9 persons) has been defined based on the utility and usefulness for anticipated search queries [6]. The concept classification was based on a multi-label CNN approach using a GoogleNet architecture [12].…”

Section: Dataset Of Historical Concepts and Personalitiesmentioning

confidence: 99%

“…Visual Concept and person recognition models have been applied to a test set of about 2,500 hours of video data and evaluated on the Top-200 retrieval results in terms of mean average precision. Therefore, the Top-200 retrieval results per class had been manually labeled by an expert [6]. For the current study, 20 concepts and 9 persons have been chosen from the GDR-specific lexicon.…”

Section: Dataset Of Historical Concepts and Personalitiesmentioning

confidence: 99%

See 1 more Smart Citation

Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historical Video Data

Pustu-Iren

Mühling

Korfhage

et al. 2019

Digital Libraries for Open Knowledge

Self Cite

View full text Add to dashboard Cite

Video indexing approaches such as visual concept classification and person recognition are essential to enable fine-grained semantic search in large-scale video archives such as the historical video collection of former German Democratic Republic (GDR) maintained by the German Broadcasting Archive (DRA). Typically, a lexicon of visual concepts has to be defined for semantic search. However, the definition of visual concepts can be more or less subjective due to individually differing judgments of annotators, which may have an impact on annotation quality and subsequently training of supervised machine learning methods. In this paper, we analyze the inter-coder agreement for historical TV data of the former GDR for visual concept classification and person recognition. The inter-coder agreement is evaluated for a group of expert as well as non-expert annotators in order to determine differences in annotation homogeneity. Furthermore, correlations between visual recognition performance and inter-annotator agreement are measured. In this context, information about image quantity and agreement are used to predict average precision for concept classification. Finally, the influence of expert vs. non-expert annotations acquired in the study are used to evaluate person recognition.

show abstract

Section: Dataset Of Historical Concepts and Personalitiesmentioning

confidence: 99%

Section: Dataset Of Historical Concepts and Personalitiesmentioning

confidence: 99%

Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historical Video Data

Pustu-Iren

Mühling

Korfhage

et al. 2019

Digital Libraries for Open Knowledge

Self Cite

View full text Add to dashboard Cite

show abstract

“…Then an automated video content analysis and retrieval system to enable the discovery of GDR TV videos in historical collections is provided. It is based on service-oriented distributed architecture and includes algorithms for shot boundary detection video analysis, idea classification, personal recognition, text recognition and similarity search [20].…”

Section: Introductionmentioning

confidence: 99%

Content based video retrieval using discrete cosine transform

Hamad

Farhan

Khudhur

2021

IJEECS

View full text Add to dashboard Cite

A content based video retrieval (CBVR)framework is built in this paper. One of the essential features of video retrieval process and CBVR is a color value. The discrete cosine transform (DCT) is used to extract a query video features to compare with the video features stored in our database. Average result of 0.6475 was obtained by using the DCT after implementing it to the database we created and collected, and on all categories. This technique was applied on our database of video, Check 100 database videos, 5 videos in each category.

show abstract

“…The archive description and its indexing [8,9], the basic information in archive information retrieval, are the foundation of retrieval technology. The process of archive description [10,11,12] is to extract the required index information and record it. The archive description should be in line with the principles that were written in the Archive Description Rules, which is formulated by the Chinese government and is used to standardize the archive description work.…”

Section: Introductionmentioning

confidence: 99%

The General Higher-Order Neural Network Model and Its Application to the Archive Retrieval in Modern Guangdong Customs Archives

Wang

Chen

2020

IEEE Access

View full text Add to dashboard Cite

Because of the unique attributes of archive information, it is challenging to manage and effectively retrieve archive information in the archive information management practice. This paper designs and develops the first general higher-order Neural Network Model for archives. Based on the analysis of the correlation, the relevance of the weight model, the study of technical methods about the core weight, the direction weight retrieval, and the statistical ranking of the results, this paper designs a corresponding archive information analysis system. Finally, this paper adopts the B/S development model by applying the relevance ranking weight algorithm into the comprehensive archive retrieval activities, which not only enhances the intelligence and efficiency of the archive retrieval, but also can act as a standard example to demonstrate informatization construction for archive management. This paper compares this algorithm with two other existing retrieval algorithms and verifies the practicability of the relevance algorithm by evaluating the algorithm and the default retrieval algorithm using the NDCG evaluation method.

show abstract

Content-based video retrieval in historical collections of the German Broadcasting Archive

Cited by 25 publications

References 38 publications

Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historical Video Data

Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historical Video Data

Content based video retrieval using discrete cosine transform

The General Higher-Order Neural Network Model and Its Application to the Archive Retrieval in Modern Guangdong Customs Archives

Contact Info

Product

Resources

About