MoCA Project: Automatic Detection and Recognition of TV
Commercials
TV commercials are interesting in many respects: advertisers and
psychologists are interested in their influence on human purchasing
habits, while parents might be interest in shielding their children
from their influence. We propose two methods for detecting and
extracting commercials in digital videos. The first method is based on
statistics of measurable features and enables the detection of
commercial blocks within TV broadcasts. The second method performs
detection and recognition of known commercials with high accuracy.
Finally, we show how both approaches can be combined into a
self-learning system. Our experimental results underline the
practicality of the methods.
Demo
Short Demo Video (MPEG-1: 28MB)
Publications
- Rainer Lienhart, Christoph Kuhmünch and Wolfgang
Effelsberg. Isolating and Identifying Commercials in TV Programs. In
Handbook of Multimedia Computing, CRC Press, 1998. [Abstract]
- Rainer Lienhart, Christoph Kuhmünch and Wolfgang
Effelsberg. Aufspüren und Erkennen von Werbung in laufenden
Fernsehsendungen. In: Mustererkennung 1997, 19. DAGM-Symposium,
Braunschweig, 15.-17. September 1997, Erwin Paulus and Friedrich M.
Wahl, Editors, pp. 435-445, September 1997. [Abstract]
[
PDF:
201
KB]
- Rainer Lienhart, Christoph Kuhmünch and Wolfgang
Effelsberg. On the Detection and Recognition of Television Commercials,
Proc. IEEE Conf. on Multimedia Computing and Systems, Ottawa, Canada,
pp. 509 - 516, June 1997. [Abstract]
[PDF:
138KB];
also Technical Report TR-96-016, Dezember 1996.