Moving object detection using optical flow


2019-11-21 22:24 Motion vectors, represents flow of a moving object, are obtained using Lucas kanade optical flow algorithm for moving object detection with complex background. These flow vectors are quantized using a predefined threshold to decide whether a pixel is a part of an object or a background.

Optical flow estimation is one of the oldest and still most active research domains in computer vision. This paper proposes a novel and efficient method of moving object area detection in the video sequence employing the normalized selfadaptive optical flow. moving object detection using optical flow detecting moving objects in digital videos. The moving detection and tracking system is developed based on optical flow estimation together with application and combination of various relevant computer vision and image processing techniques to enhance the process. To

This paper presents a pedestrian detection method from a moving vehicle using optical flows and histogram of oriented gradients (HOG). A moving object is extracted from the relative motion by segmenting the region representing the same optical flows after compensating the egomotion of the camera. To obtain the optical flow, two consecutive images are divided into grid cells pixels; then each moving object detection using optical flow

has done and still going on about tracking of objects in input videos. The object tracking system using Kalman filter and Optical flow is proposed in [1. The tracking algorithm is designed to track multiple moving objects in the input video. The optical flow is used as object detection mechanism. How can the answer be improved? This paper presents a pedestrian detection method from a moving vehicle using optical flows and histogram of oriented gradients (HOG). A moving object is extracted from the relative motion by segmenting the region representing the same optical flows moving object detection using optical flow



Gallery Moving object detection using optical flow