Identifying relevant frames in weakly labeled videos for training concept detectors

CIVR 2008 - Proceedings of the International Conference on Content-based Image and Video Retrieval

Volumn , Issue , 2008, Pages 9-16

  Ulges, Adrian ^a   Keysers, Daniel ^b   Schulze, Christian ^a   Breuel, Thomas M ^b  

^a Rheinland Pfälzische Technische Universität Kaiserslautern Landau   (Germany)

^b GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

Author keywords

Content based video retrieval; Online videos; Video tagging

Indexed keywords

IMAGE SEGMENTATION; INFORMATION THEORY; RANDOM VARIABLES;

AUTOMATIC DETECTIONS; CONTENT-BASED VIDEO RETRIEVAL; GROUND TRUTHS; KEY PROBLEMS; KEY-FRAMES; ONLINE VIDEOS; PROBABILISTIC FRAMEWORKS; QUANTITATIVE EXPERIMENTS; REAL-WORLD; SEMANTIC CONCEPTS; TRAINING DATUM; TRAINING SETS; TV NEWS; VIDEO STREAMS; VIDEO TAGGING;

IMAGE RETRIEVAL;

EID: 57549109095     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1386352.1386358     Document Type: Conference Paper

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