Foveated shot detection for video segmentation

被引:67
作者
Boccignone, G [1 ]
Chianese, A
Moscato, V
Picariello, A
机构
[1] Univ Salerno, Dipartimento Ingn Informaz & Ingn Electtr, I-84084 Salerno, Italy
[2] Univ Naples Federico II, Dipartimento Informat & Sistemist, I-80125 Naples, Italy
关键词
attentive vision; dissolves; hard cuts; shot detection; video segmentation;
D O I
10.1109/TCSVT.2004.842603
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We view scenes in the real world by moving our eyes three to four times each second and integrating information across subsequent fixations (foveation points). By taking advantage of this fact, in this paper we propose an original approach to partitioning of a video into shots based on a foveated representation of the video. More precisely! the shot-change detection method is related to the computation, at each time instant, of a consistency measure of the fixation sequences generated by an ideal observer looking at the video. The proposed scheme aims at detecting both abrupt and gradual transitions between shots using a single technique, rather than a set of dedicated methods. Results on videos of various content types are reported and validate the proposed approach.
引用
收藏
页码:365 / 377
页数:13
相关论文
共 64 条
[1]   Humanoid robots: A new kind of tool [J].
Adams, B ;
Breazeal, C ;
Brooks, RA ;
Scassellati, B .
IEEE INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 2000, 15 (04) :25-31
[2]  
[Anonymous], 1997, A Wavelet Tour of Signal Processing
[3]  
[Anonymous], 2001, Int. J. Image Graph., DOI DOI 10.1142/S021946780100027X
[4]   A survey on the use of pattern recognition methods for abstraction, indexing and retrieval of images and video [J].
Antani, S ;
Kasturi, R ;
Jain, R .
PATTERN RECOGNITION, 2002, 35 (04) :945-965
[5]  
Ba Tu Truong, 2000, Proceedings ACM Multimedia 2000, P219, DOI 10.1145/354384.354481
[6]   Data- and model-driven gaze control for an active-vision system [J].
Backer, G ;
Mertsching, B ;
Bollmann, M .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2001, 23 (12) :1415-1429
[7]   TEMPORAL WINNER-TAKE-ALL NETWORKS - A TIME-BASED MECHANISM FOR FAST SELECTION IN NEURAL NETWORKS [J].
BARNDEN, JA ;
SRINIVAS, K .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1993, 4 (05) :844-853
[8]  
Berthoz Alain., 1997, SENS MOUVEMENT
[9]   Modelling gaze shift as a constrained random walk [J].
Boccignone, G ;
Ferraro, M .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2004, 331 (1-2) :207-218
[10]  
Broadbent DE, 1958, PERCEPTION COMMUNICA