Proceedings ArticleDOI
Soccer Video Retrival Using Adaptive Time-Frequency Methods
J. Marchal,Cornel Ioana,Emanuel Radoi,André Quinquis,Sridhar Krishnan +4 more
- Vol. 5, pp 509-512
TLDR
The results provided will prove the efficiency of the adaptive time-frequency representation as a feature extraction stage and the matching pursuit concept and a dictionary composed of Gabor functions.Abstract:
The retrieval of soccer highlights is a suitable technique for video indexing, required by the multimedia database management or for the development of television on demand. For these purposes, it should be interesting to have an automatic annotation of events happened in soccer games. One solution consists in analyzing the audio soundtrack associated to the soccer video and to detect the interesting frames. In this paper we use the adaptive time-frequency decomposition of the soundtrack as a feature extraction procedure. This decomposition is based on the Matching Pursuit concept and a dictionary composed of Gabor functions. The parameters provided by these transformations constitute the input of the classification stage. The results provided for real soccer video will prove the efficiency of the adaptive time-frequency representation as a feature extraction stage.read more
Citations
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Proceedings ArticleDOI
3D wavelet video coding with replicated matching pursuits
Yuan Yuan,Donald M. Monro +1 more
TL;DR: Improved coding of 3D spatio-temporal wavelet video is achieved using matching pursuits (MP) with a separable 2D basis dictionary and temporal replication of atoms to achieve significant gains at low bit rates.
Dissertation
Caratérisation des signaux non-stationnaires à composantes temps-fréquence non-linéaires
TL;DR: La definition des distributions a temps complexe a constitue le troisieme axe, which nous a permis de definir la classe des methodes de suivi temps-frequence-phaseen utilisant egalement des techniques de modelisation polynomiale de phase ainsi that le principe du tracking par the methode of Viterbi.
Optimized dictionary design and classification using the matching pursuits dissimilarity measure
TL;DR: A matching pursuits dissimilarity measure (MPDM) is developed that is capable of performing shape-based comparisons between very high-dimensional signals and has been used with the competitive agglomeration fuzzy clustering algorithm to develop a prototype-based probabilistic classifier, called CAMP.
References
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Book
A wavelet tour of signal processing
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Journal ArticleDOI
Matching pursuits with time-frequency dictionaries
Stéphane Mallat,Zhifeng Zhang +1 more
TL;DR: The authors introduce an algorithm, called matching pursuit, that decomposes any signal into a linear expansion of waveforms that are selected from a redundant dictionary of functions, chosen in order to best match the signal structures.
Proceedings ArticleDOI
Automatic parsing of TV soccer programs
TL;DR: The proposed system can classify a sequence of soccer frames into various play categories, such as shot at left goal, top left corner kick play in right penalty area, in midfield, etc, based on a priori model comprising four major components: a soccer court, a ball, the players and the motion vectors.