OBJECT TRACKING AND DETECTION USING MOTION STABILIZATION TECHNIQUE
Keywords:
Background Subtraction, Object Detection, Object Tracking, Visual Attention, Motion Stabilization.Abstract
a video stabilization algorithm based on the extraction and tracking of Scale Invariant Feature Transform features through video frames. Implementation of SIFT operator is analysed and adapted to be used in a featurebased motion estimation algorithm. Object detection and tracking are important and challenging tasks in many computer vision applications such as surveillance, vehicle navigation, and autonomous robot navigation. Video surveillance in a dynamic environment, especially for humans and vehicles, is one of the current challenging research topics in computer vision. Tracking is usually performed in the context of higher-level applications that require the location and/or shape of the object in every frame. in this article proposing real time multiple moving object detection
method. Scale invariant feature transformation (SIFT) algorithm is used to extracting the features from videos. The motion stabilization algorithm is user to track the moving object. We propose a tracking method which tracks the complete object regions. Intentionally camera motion is eventually filtered with Adaptive Motion vector Integration
