5 years of work experience as a software test engineer in an agile development environment. Specialize in Black Box, White Box, Unit, Functionality and case-specific testing procedures. ©

Intelligent Video Analytics Video Analysis and Computer Vision; Framework for Action Detection based on event; deep learning for robot vision; Video Analysis for Machine Intelligence; Vision-Based System for Automated Human Behavior Recognition; A Large-scale Benchmark Dataset for Event Recognition in Surveillance Video Activity, Event and Action Databases; tiziran (at) gmail; OpenCV 3.x, Visual Studio 2013, Windows 64bit, CUDA, for Deep-learning: use opencv_dnn module for image classification by using GoogLeNet trained network; Framework of Violent detection; Convolutional neural network (CNN) {deep learning}; MoSIFT: Recognizing Human Actions in Surveillance Videos; HOOF: Histogram of Oriented Optical Flow ; HOFM: Histograms of Optical Flow Orientation and Magnitude to Detect Anomalous Events in Videos; Crowd Behavior Analysis; intelligent surveillance for smart home; visual surveillance for intelligent robot; provide a secure environment to people, automatic environment surveillance, violent scenes detection, automatic classification system for violent videos in order to protect children to reach violent contents. event video analysis, analyze the scene, detection and recognition of suspicious activities. elderly care system. automatic recognition of human action or type of behavior; human motion and activity need high-level understanding of video, video retrieval, video summarization, dynamic system recognition, analysis of dynamic scenes. motion history image (MHI); updateMotionHistory; Time series features; Principal component analysis; human behavior /behaviour analysis;Image Signal Processor (ISP);video and image stabilization; depth map; depth of field; sharpness image;Motion Analysis and Object Tracking ©