The Semantic Pathfinder for Generic News Video Indexing

This paper presents the semantic pathfinder archtiecture for
generic indexing of video archives. The pathfinder automatically
extracts semantic concepts from video based on the exploration of
different paths through three consecutive analysis steps, closely
linked to the video production process, namely: content analysis,
style analysis, and context analysis. The virtue of the semantic
pathfinder is its learned ability to find a best path of analysis
steps on a per-concept basis. To show the generality of this
indexing approach we develop detectors for a lexicon of 32
concepts and we evaluate the semantic pathfinder against the 2004
NIST TRECVID video retrieval benchmark, using a news archive of 64
hours. Top ranking performance indicates the merit of the semantic
pathfinder.