Object-based video synopsis and multi-video body retrieval

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.

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Moving Object Based Collision-Free Video Synopsis

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ◽

10.1109/smc.2018.00287 ◽

2018 ◽

Author(s):

Anton Jeran Ratnarajah ◽

Sahani Goonetilleke ◽

Dumindu Tissera ◽

Kapilan Balagopalan ◽

Ranga Rodrigo

Keyword(s):

Moving Object ◽

Video Synopsis ◽

Object Based

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Algorithm of Surveillance Video Synopsis Based on Objects

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.321-324.1041 ◽

2013 ◽

Vol 321-324 ◽

pp. 1041-1045

Author(s):

Jian Rong Cao ◽

Yang Xu ◽

Cai Yun Liu

Keyword(s):

Moving Objects ◽

Background Modeling ◽

Moving Object ◽

Experimental Results ◽

Single Camera ◽

Surveillance Video ◽

Video Synopsis ◽

Object Based ◽

Camera Surveillance ◽

Background Image

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.

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Query-By-Object Based Video Synopsis

2021 International Conference on Intelligent Technologies (CONIT) ◽

10.1109/conit51480.2021.9498311 ◽

2021 ◽

Author(s):

Shweta S Kakodra ◽

C Sujatha ◽

Padmashree Desai

Keyword(s):

Video Synopsis ◽

Object Based

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Object-Based Surveillance Video Synopsis Using Genetic Algorithm

Censorship, Surveillance, and Privacy ◽

10.4018/978-1-5225-7113-1.ch044 ◽

2019 ◽

pp. 857-883

Author(s):

Shefali Gandhi ◽

Tushar V. Ratanpara

Keyword(s):

Genetic Algorithm ◽

Background Subtraction ◽

Moving Objects ◽

Time Lapse ◽

Original Video ◽

Surveillance Video ◽

Time Activity ◽

Video Synopsis ◽

Object Based ◽

Poisson Image Editing

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.

Download Full-text