Information-Theoretic Framework for The Joint Temporal Partionning and Representation of Video Data
Bruno Janvier, Éric Bruno, Stéphane Marchand‐Maillet, Thierry Pun · Archive ouverte UNIGE (University of Geneva) · 2003
The first step in the analysis of video content is the partitioning of a long video sequence into short homogeneous temporal segments.The homogeneity property ensures that the segments are taken by a single camera and represent a continuous action in time and space.These segments will then be used as atomic temporal components for higher level analysis like browsing, classification, indexing and retrieval.The novelty of our approach is to use color information to cut down the video into segments dynamically homogeneous using a criterion inspired by compact coding theory.First, we use a statistical detection framework to detect abrupt "shot" transitions (strong discontinuities in the data stream), then, we perform an information-based segmentation inside each "shot" using a Minimum Message Length (MML) criterion and minimization by a Dynamic Programming Algorithm (DPA).We show that our method is robust to detect all types of transitions in a generic manner.A specific detector for each type of transition of interest becomes unnecessary.We give two examples of applications : shot boundaries detection and keyframe selection.