Detection of Abnormal Behaviors Based on Spatial Analysis for Intelligent Video Surveillance systems

نویسندگان

  • Fatemeh Ziaeetabar
  • Nasrollah Moghadam Charkari
چکیده

Video surveillance technology is one of the most important topics in the security technology domain. However, the existing video surveillance systems relay on human observers and have some limitations. Therefore, it is necessary these systems equipped to an internal intelligence and detect abnormality automatically. In this paper, we have proposed a novel method for recognizing abnormal behaviors based on the spatial analysis. We have studied both misuse detection and anomaly detection approaches and compared their results. Misuse detection is related to definition of suspicious area in the dataset scene while anomaly detection clusters the scene to some regions by considering the abundance of the people passing. In addition, we have defined a new parameter which decision about level of abnormality is determined according it. It can update automatically from new input behaviors. Experimental results which have been done on the CAVIAR dataset indicate our method has an accuracy of 92% and it is almost compatible with the hand labeled results.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

استفاده از نمایش پراکنده و همکاری دوربین‌ها برای کاربردهای نظارت بینایی

With the growth of demand for security and safety, video-based surveillance systems have been employed in a large number of rural and urban areas. The problem of such systems lies in the detection of patterns of behaviors in a dataset that do not conform to normal behaviors. Recently, for behavior classification and abnormal behavior detection, the sparse representation approach is used. In thi...

متن کامل

Anomalous Event Detection in Traffic Video Surveillance Based on Temporal Pattern Analysis

Traffic video surveillance has received significant attention in recent years. Anomalous Event Detection is gaining popularity among vision community. Existing methods on Intelligent Traffic Surveillance (ITS) systems are inefficient in detecting abnormal events, as they employ high level object features. This paper proposes an alternate solution named Optical Flow based Frequent Pattern Mining...

متن کامل

Application of Combined Local Object Based Features and Cluster Fusion for the Behaviors Recognition and Detection of Abnormal Behaviors

In this paper, we propose a novel framework for behaviors recognition and detection of certain types of abnormal behaviors, capable of achieving high detection rates on a variety of real-life scenes. The new proposed approach here is a combination of the location based methods and the object based ones. First, a novel approach is formulated to use optical flow and binary motion video as the loc...

متن کامل

Fire detection using video sequences in urban out-door environment

Nowadays automated early warning systems are essential in human life. One of these systems is fire detection which plays an important role in surveillance and security systems because the fire can spread quickly and cause great damage to an area. Traditional fire detection methods usually are based on smoke and temperature detectors (sensors). These methods cannot work properly in large space a...

متن کامل

Traffic Scene Analysis using Hierarchical Sparse Topical Coding

Analyzing motion patterns in traffic videos can be exploited directly to generate high-level descriptions of the video contents. Such descriptions may further be employed in different traffic applications such as traffic phase detection and abnormal event detection. One of the most recent and successful unsupervised methods for complex traffic scene analysis is based on topic models. In this pa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012