Temporal Video Segmentation Using Optical Flow Estimation

Moving Objects Segmentation Using Optical Flow Estimation

In this paper, we present a new method for the segmentation of moving objects. We use one of the most powerful variational method for computing the optical flow and we exploit this information in the segmentation. This segmentation lies on well-known techniques of active contours. Since we can distinguish moving objects from static elements of a scene by analyzing norm of the optical flow vecto...

Temporal Video Segmentation Using Unsupervised

This paper proposes a content-based temporal video segmentation system that integrates syntactic (domain-independent) and semantic (domain-dependent) features for automatic management of video data. Temporal video segmentation includes scene change detection and shot classiication. The proposed scene change detection method consists of two steps: detection and tracking of semantic objects of in...

Fire Detection in Video Sequences using Optical Flow Estimation

Vision-based flame detection can be applied in large open spaces for fire detection, which has been achieved with camera surveillance systems. The motion estimator exploits some motion features such as color, shape and texture that are used to recognize fire and non-fire region. Classical systems applied optical flow estimation methods for flame detection which are based on the assumptions, for...

Motion estimation in video coding using simplified optical flow technique

We propose an interpolation-free sub-pixel Motion Estimation (ME) technique that particularly aims at providing accurate Motion Vectors (MVs), where conventional sub-pixel interpolation ME algorithms used in video coding are too complex and time consuming. The proposed algorithm is a combination of block matching algorithms and simplified optical flow, which is Taylor approximation. The techniq...

Segmentation and Estimation of the Optical Flow