Video abstraction and summarization, being request in several applications, has address a number of researches to automatic video analysis techniques. The processes for automatic video analysis are based on the recognition of short sequences of contiguous frames that describe the same scene, shots, and key frames representing the salient content of the shot. Since effective shot boundary detection techniques exist in the literature, in this paper we will focus our attention on key frames extraction techniques to identify the low level visual features of the frames that better represent the shot content. To evaluate the features performance, key frame automatically extracted using these features, are compared to human operator video annotations.
Image feature meaning for automatic key-frame extraction / Di Lecce, Vincenzo; Guerriero, Andrea. - STAMPA. - 5307:(2004), pp. 319-328. (Intervento presentato al convegno Conference on Storage and Retrieval Methods and Applications for Multimedia tenutosi a San Jose, CA nel January 20-22, 2004) [10.1117/12.526706].
Image feature meaning for automatic key-frame extraction
Vincenzo Di Lecce;Andrea Guerriero
2004-01-01
Abstract
Video abstraction and summarization, being request in several applications, has address a number of researches to automatic video analysis techniques. The processes for automatic video analysis are based on the recognition of short sequences of contiguous frames that describe the same scene, shots, and key frames representing the salient content of the shot. Since effective shot boundary detection techniques exist in the literature, in this paper we will focus our attention on key frames extraction techniques to identify the low level visual features of the frames that better represent the shot content. To evaluate the features performance, key frame automatically extracted using these features, are compared to human operator video annotations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
