Machine Learning Methods from Group to Crowd Behaviour Analysis

被引：5

作者：

Felipe Borja-Borja, Luis ^{[1
]}

Saval-Calvo, Marcelo ^{[2
]}

Azorin-Lopez, Jorge ^{[2
]}

机构：

[1] Univ Cent Ecuador, Ciudadela Univ Av Amer, Quito, Ecuador

[2] Univ Alicante, Comp Technol Dept, Carretera San Vicente S-N, San Vicente Del Raspeig 03690, Spain

来源：

ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2017, PT II | 2017年 / 10306卷

关键词：

Human behavior analysis; Motion analysis; Trajectory analysis; Machine learning; Crowd automated analysis; Computer vision; ACTIVITY RECOGNITION; REPRESENTATION; SURVEILLANCE; MODEL;

D O I：

10.1007/978-3-319-59147-6_26

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The human behaviour analysis has been a subject of study in various fields of science (e.g. sociology, psychology, computer science). Specifically, the automated understanding of the behaviour of both individuals and groups remains a very challenging problem from the sensor systems to artificial intelligence techniques. Being aware of the extent of the topic, the objective of this paper is to review the state of the art focusing on machine learning techniques and computer vision as sensor system to the artificial intelligence techniques. Moreover, a lack of review comparing the level of abstraction in terms of activities duration is found in the literature. In this paper, a review of the methods and techniques based on machine learning to classify group behaviour in sequence of images is presented. The review take into account the different levels of understanding and the number of people in the group.

引用

页码：294 / 305

页数：12

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