International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
www.irjet.net
Video Stabilization using Python and open CV Swetaj Mangesh Mohite1, Kumarswami Mangesh Mhashilkar2, Prem Praful Morey3 , Prof. Vilas Jadhav4 1,2,3
4
Students, Department of Computer Engineering, MGM College of Engineering & Technology, Kamothe, Navi Mumbai, Maharashtra, India.
Assistant Professor, Department of Computer Engineering, MGM College of Engineering & Technology, Kamothe, Navi Mumbai, Maharashtra, India. ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Video stabilization is an important technique
video frames and using their movement to stabilize the footage.
used to reduce unwanted camera motion in videos. In this paper, we propose a video stabilization method that utilizes point feature matching to estimate the camera motion between consecutive frames. The proposed method first extracts point features from the input video frames using the she Tomasi corner detection algorithm. Next, it matches the point features between consecutive frames to estimate the camera motion. Finally, the estimated camera motion is used to stabilize the video by applying a geometric transformation to the frames.
Point feature matching algorithms are highly effective in stabilizing videos, even in challenging conditions such as moving cameras, low light, or dynamic scenes. They also have a wide range of applications, including in film and video production, surveillance, and sports broadcasting. However, they require powerful computing resources and can be computationally intensive, especially for highresolution and high-frame-rate videos.
To evaluate the proposed method, we conducted experiments on a dataset of handheld videos captured using a smartphone camera. Our experiments show that the proposed method can effectively reduce unwanted camera motion in the input videos, resulting in smoother and more visually pleasing stabilized videos. Furthermore, the proposed method outperforms several state-of-the-art video stabilization methods in terms of both visual quality and computational efficiency.
In this paper, we will explore the concept of video stabilization using point feature matching in more detail, including the underlying principles, techniques, and applications. We will also discuss the advantages and limitations of this approach and compare it with other video stabilization methods. Finally, we will demonstrate the effectiveness of point feature matching using real-world examples and provide practical tips for implementing it in your own video production workflow.
Key Words: Video stabilization, point feature matching, Shi-Tomasi corner detection, camera motion estimation, geometric transformation, handheld videos, smartphone camera.
along with the reference number in the running text. The order of reference in the running text should match with the list of references at the end of the paper.
2.PROBLEM STATEMENT
1.INTRODUCTION
The problem of unwanted camera motion in video footage is a common issue that can impact the quality of video content. Traditionally, the solution to this problem was to use mechanical approaches to stabilize the camera, such as tripods, gimbals, or steady-cams. However, these methods are not always practical or feasible, especially in dynamic environments or when using handheld devices. Additionally, these mechanical approaches can be expensive and limit the range of motion of the camera.
Video stabilization is the process of removing unwanted shakiness and motion from a video to produce a smoother and more professional-looking footage. The traditional method of video stabilization involves physically stabilizing the camera, either by using a tripod or other stabilizing equipment. However, this approach is not always practical, especially when filming in challenging conditions or when using handheld devices.
As a result, digital video stabilization techniques have been developed to address this problem. However, these techniques often require specialized software and hardware that can be expensive and require high processing power. Additionally, many software approaches for video stabilization rely on new technologies and research, which can limit their accessibility and increase their cost.
In recent years, digital video stabilization techniques have gained popularity, which uses software algorithms to remove unwanted camera motion in post-processing. One of the popular approaches for digital video stabilization is using point feature matching, which involves identifying and tracking specific points in the
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