Real Time Motion Detection Video Surveillance For Categorizing Between Human and Non-Human - Jain, Meghna; Agarwal, Kriti; Sheth, Vrajesh; (Mohite), ,Vaishali Gaikwad (IJRDO -Journal of Computer Science Engineering, 2015)
An Automated Video Surveillance andmonitoring system has a rich history. Traditional videosurveillance systems are large in number but stillretrenched in an extensive manner. The system targetsat tracking an object and segregates it as Human orNon-Human entities, wherein the non-human entitieswould be further analysed into its respective categorieswhich would help in subsequent analytics.The systemwhen recognizes suspicious activity, it is capturedinstantly and the alarm is triggered for the securitypurpose. It is necessary to introduce an application thatautomatically formulates the images captured in orderto detect precarious situations or undesirableencroached objects. Object detection is a mandatorystep in automated video surveillance. Foregroundextraction in harmony with background subtraction isfurther collaborated with the thresholded image forrevelation of entities. The system engages acontemporary combination of Background Modelling,Support vector machine (SVM) and a Human Detectionfor Surveillance (HDS) System. The HDS systemassimilates a Histogram of Oriented Gradients based ona human detector which is in limelight for itsperformance in detecting humanistic appearances.Detailed analysis is carried out on the performance ofthe system on various test videos.