Retraction Note to: A kernel support vector machine based anomaly detection using spatio-temporal motion pattern models in extremely crowded scenes
نویسندگان
چکیده
منابع مشابه
Spatio-Temporal Motion Pattern Modeling of Extremely Crowded Scenes
The abundance of video surveillance systems has created a dire need for computational methods that can assist or even replace human operators. Research in this field, however, has yet to tackle an important real-world scenario: extremely crowded scenes. The excessive amount of people and their activities in extremely crowded scenes present unique challenges to motion-based video analysis. In th...
متن کاملMODELING OF FLOW NUMBER OF ASPHALT MIXTURES USING A MULTI–KERNEL BASED SUPPORT VECTOR MACHINE APPROACH
Flow number of asphalt–aggregate mixtures as an explanatory factor has been proposed in order to assess the rutting potential of asphalt mixtures. This study proposes a multiple–kernel based support vector machine (MK–SVM) approach for modeling of flow number of asphalt mixtures. The MK–SVM approach consists of weighted least squares–support vector machine (WLS–SVM) integrating two kernel funct...
متن کاملAnomaly Detection using Support Vector Machine
Support vector machine are among the most well known supervised anomaly detection technique, which are very efficient in handling large and high dimensional dataset. SVM, a powerful machine method developed from statistical learning and has made significant achievement in some field. This Technique does not suffer the limitations of data dimensionality and limited samples. In this present study...
متن کاملDensity aware anomaly detection in crowded scenes
Coherent nature of crowd movement allows representing the crowd motion using sparse features. However, surveillance videos recorded at different periods of time are likely to have different crowd densities and motion characteristics. These varying scene properties necessitate use of different models for an effective representation of behaviour at different periods. In this study, a density awar...
متن کاملContextual anomaly detection in crowded surveillance scenes
This work addresses the problem of detecting human behavioural anomalies in crowded surveillance environments. We focus in particular on the problem of detecting subtle anomalies in a behaviourally heterogeneous surveillance scene. To reach this goal we implement a novel unsupervised context-aware process. We propose and evaluate a method of utilising social context and scene context to improve...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Ambient Intelligence and Humanized Computing
سال: 2022
ISSN: ['1868-5137', '1868-5145']
DOI: https://doi.org/10.1007/s12652-022-04013-6