Social Groups Detection by Using Support Vector Machine in Video

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AKBARI ALI; FARSI HASSAN; MOHAMADZADEH SAJAD

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Paper Information

Journal: JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT) Year:2019 | Volume:8 | Issue:3 Page(s): 1-9

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Title

Social Groups Detection by Using Support Vector Machine in Video

Author(s)

AKBARI ALI | FARSI HASSAN | MOHAMADZADEH SAJAD | Issue Writer Certificate

Keywords

Detecting Social GroupsQ1

Physical DistanceQ1

Temporal CausalityQ1

Shape SimilarityQ1

Crowd PlaceQ1

Abstract

Detecting Social Groups is one of important and complex problems which has been concerned recently. Detecting Social Groups and relation between group members will be necessary for human robots in near future. Databases have some information including trajectories and also labels of members. The target is to detect social groups that contains at least two people or detecting individual motion of the people. In the proposed method, for Detecting Social Groups, Physical Distance, Temporal Causality and Shape Similarity features are used. The required time to extract these features is lower than the other suggested features. In addition to precession and recall, the effectiveness of the proposed method in terms of required time for training and testing data is also examined. Lower required time provides greater ability to implement for human robots. The proposed method provides acceptable results in valid databases and is compared to existing methods in terms of statistical results and the required time.

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APA: Copy

AKBARI, ALI, FARSI, HASSAN, & MOHAMADZADEH, SAJAD. (2019). Social Groups Detection by Using Support Vector Machine in Video. JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT), 8(3 ), 1-9. SID. https://sid.ir/paper/245857/en

Vancouver: Copy

AKBARI ALI, FARSI HASSAN, MOHAMADZADEH SAJAD. Social Groups Detection by Using Support Vector Machine in Video. JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT)[Internet]. 2019;8(3 ):1-9. Available from: https://sid.ir/paper/245857/en

IEEE: Copy

ALI AKBARI, HASSAN FARSI, and SAJAD MOHAMADZADEH, “Social Groups Detection by Using Support Vector Machine in Video,” JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT), vol. 8, no. 3 , pp. 1–9, 2019, [Online]. Available: https://sid.ir/paper/245857/en

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