Detection of salient regions in crowded scenes
نویسندگان
چکیده
منابع مشابه
Detection of Salient Regions in Crowded Scenes
ELECT The increasing number of cameras and a handful of human operators to monitor the video inputs from hundreds of cameras leave the system ill equipped to fulfil the task of detecting anomalies. Thus, there is a dire need to automatically detect the regions that require immediate attention for more effective and proactive surveillance. A framework that utilises the temporal variations in the...
متن کاملOnline multiple people tracking-by-detection in crowded scenes
Multiple people detection and tracking is a challenging task in real-world crowded scenes. In this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. We have detected objects with deformable part models and a visual background extractor. In the tracking phase we have used a combination of support vector machine (SVM) person-specific classifie...
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 کاملHead Detection in Densely Crowded Scenes
............................................................................. i ACKNOWLEDGEMENTS .............................................................. ii CONTENTS ............................................................................... iii LIST OF FIGURES ....................................................................... vi LIST OF TABLES ......................................
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: Electronics Letters
سال: 2014
ISSN: 0013-5194,1350-911X
DOI: 10.1049/el.2013.3993