Object-based video synopsis and multi-video body retrieval

2016 ◽  
Vol 5 (0) ◽  
pp. 7
Author(s):  
Yi Guo ◽  
Su-Rong Qi-Mu ◽  
Wei Jin ◽  
Xing Wei
Keyword(s):  
Author(s):  
Shefali Gandhi ◽  
Tushar V. Ratanpara

Video synopsis provides representation of the long surveillance video, while preserving the essential activities of the original video. The activity in the original video is covered into a shorter period by simultaneously displaying multiple activities, which originally occurred at different time segments. As activities are to be displayed in different time segments than original video, the process begins with extracting moving objects. Temporal median algorithm is used to model background and foreground objects are detected using background subtraction method. Each moving object is represented as a space-time activity tube in the video. The concept of genetic algorithm is used for optimized temporal shifting of activity tubes. The temporal arrangement of tubes which results in minimum collision and maintains chronological order of events is considered as the best solution. The time-lapse background video is generated next, which is used as background for the synopsis video. Finally, the activity tubes are stitched on the time-lapse background video using Poisson image editing.


Author(s):  
Anton Jeran Ratnarajah ◽  
Sahani Goonetilleke ◽  
Dumindu Tissera ◽  
Kapilan Balagopalan ◽  
Ranga Rodrigo

2013 ◽  
Vol 321-324 ◽  
pp. 1041-1045
Author(s):  
Jian Rong Cao ◽  
Yang Xu ◽  
Cai Yun Liu

After background modeling and segmenting of moving object for surveillance video, this paper firstly presented a noninteractive matting algorithm of video moving object based on GrabCut. These matted moving objects then were placed in a background image on the condition of nonoverlapping arrangement, so a frame could be obtained with several moving objects placed in a background image. Finally, a series of these frame images could be achieved in timeline and a single camera surveillance video synopsis could be formed. The experimental results show that this video synopsis has the features of conciseness and readable concentrated form and the efficiency of browsing and retrieval can be improved.


Author(s):  
Shefali Gandhi ◽  
Tushar V. Ratanpara

Video synopsis provides representation of the long surveillance video, while preserving the essential activities of the original video. The activity in the original video is covered into a shorter period by simultaneously displaying multiple activities, which originally occurred at different time segments. As activities are to be displayed in different time segments than original video, the process begins with extracting moving objects. Temporal median algorithm is used to model background and foreground objects are detected using background subtraction method. Each moving object is represented as a space-time activity tube in the video. The concept of genetic algorithm is used for optimized temporal shifting of activity tubes. The temporal arrangement of tubes which results in minimum collision and maintains chronological order of events is considered as the best solution. The time-lapse background video is generated next, which is used as background for the synopsis video. Finally, the activity tubes are stitched on the time-lapse background video using Poisson image editing.


Author(s):  
Catherine M. Arrington ◽  
Dale Dagenbach ◽  
Maura K. McCartan ◽  
Thomas H. Carr
Keyword(s):  

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