Adaptive rule-based recognition of events in video sequences

14 years 6 months ago

Download cbim.rutgers.edu

Knowledge-based fuzzy inference and neural learning are used in this paper in order to model the event recognition task in semantic video analysis. The advantage of their use is the symbolic nature of the representation of the knowledge concerning the events to be recognized. Moreover, this knowledge can be adapted with the aid of data taken from video sequences. The proposed system has been tested in soccer video sequences for detecting some complex predetermined (and represented in the form of rules) events.

Vassilis Tzouvaras, Gabriel Tsechpenakis, Giorgos

Real-time Traffic

ICIP 2003 | Image Processing | Knowledge-based Fuzzy Inference | Semantic Video Analysis | Soccer Video Sequences |

claim paper

» A proposal for high compression of faces in video sequences using adaptive eigenspaces

» Recognizing Human Actions A Local SVM Approach

» VideoBased Face Recognition Using Adaptive Hidden Markov Models

» RealTime Video Surveillance with SelfOrganizing Maps

» Video Event Classification Using Bag of Words and String Kernels

» Clustering of Trajectories in Video Surveillance Using Growing Neural Gas

» Activity Recognition from Video Sequences using Declarative Models

» Goal Recognition with Markov Logic Networks for PlayerAdaptive Games

Post Info
More Details (n/a)

Added	24 Oct 2009
Updated	24 Oct 2009
Type	Conference
Year	2003
Where	ICIP
Authors	Vassilis Tzouvaras, Gabriel Tsechpenakis, Giorgos B. Stamou, Stefanos D. Kollias

Comments (0)

Sciweavers

Adaptive rule-based recognition of events in video sequences

ICIP 2003 | Image Processing | Knowledge-based Fuzzy Inference | Semantic Video Analysis | Soccer Video Sequences |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers