Semantic Analysis for Automatic Event Recognition and Segmentation of Wedding Ceremony Videos

Abstract

Abstract-Wedding is one of the most important ceremonies in our lives. It symbolizes the birth and creation of a new family. In this paper, we present a system for automatically segmenting a wedding ceremony video into a sequence of recognizable wedding events, e.g. the couple's wedding kiss. Our goal is to develop an automatic tool that helps users to efficiently organize, search, and retrieve his/her treasured wedding memories. Furthermore, the obtained event descriptions could benefit and complement the current research in semantic video understanding. Based on the knowledge of wedding customs, a set of audiovisual features, relating to the wedding contexts of speech/music types, applause activities, picture-taking activities, and leading roles, are exploited to build statistical models for each wedding event. Thirteen wedding events are then recognized by a hidden Markov model, which takes into account both the fitness of observed features and the temporal rationality of event ordering to improve the segmentation accuracy. We conducted experiments on a collection of wedding videos and the promising results demonstrate the effectiveness of our approach. Comparisons with conditional random fields show that the proposed approach is more effective in this application domain.

Recent Advances on Video Coding

“…For instance, the background except the couple in the wedding video can be compressed with a higher rate than the area of the bride and groom because of its lower semantic importance (less interesting to humans). Many researches (Cheng et al, 2008;Bertini et al, 2006;Ng et al, 2010) investigate methodologies for analyzing the semantic meaning of the video. Within the MPEG-7 (ISO/IEC 15938) Multimedia Description Schemes specification, "event" is used in the Creation and Production description tools to describe the agents and tools involved in creation process.…”

“…Besides the finite sate machine, the Hidden Markov Model (Rabiner, 1989) is another common tool for modelling the content event. Based on the observation of wedding events, including speech/music types, applause activities, picture-taking activities, and leading roles, Cheng et al (2008) exploited an HMM framework for segmenting wedding videos, which integrates the wedding event statistical models and the event transition model. Fig.…”