Papers by shamsundar kulkarni
Abstract: Video capturing by non-professionals will lead to unanticipated effects. such as image ... more Abstract: Video capturing by non-professionals will lead to unanticipated effects. such as image distortion, image blurring etc. Many researchers focused on these drawbacks to enhance the quality of videos. In this paper an algorithm based on s-R-t transform is proposed to stabilize jittery videos .A stable output video is obtained without the effect of jitter which is caused due to shaking of handheld camera during video recording. In this technique firstly, salient points from each frame from the input video are identified using FAST algorithm. Camera motion is corrected by affine transform and motion compensation is performed by s-R-t transform which gives stabilized video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.
Journal of Physics: Conference Series
Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion... more Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper an algorithm is proposed to stabilize jittery videos. A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video is identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.
International Journal of Signal and Imaging Systems Engineering
Advances in Image and Video Processing, 2017
In order to stabilize a video sequence we need to find a transformation which reduces the distort... more In order to stabilize a video sequence we need to find a transformation which reduces the distortion between frames. To find this transformation feature points must be identified in consecutive frames. In order to get the correspondences between feature points Sum of Squared Differences (SSD) is adopted as matching cost between respective points but by this technique, many of the point correspondences are obtained and they have limited accuracy. To rectify this dilemma, Random Sample Consensus (RANSAC) algorithm is used which is implemented in the Geometric Transform function in Matlab. Utilizing the Random Sample Consensus (RANSAC) algorithm, a robust estimate of transformation between consecutive video frames could possibly be derived. In this paper RANSAC algorithm can be used to find effective inlier correspondences and afterward it derives the affine transformation to map the inliers in consecutive video frames. This transformation is capable to improve the image plane .The RANSAC algorithm is repeated multiple times and at each run the cost of the end result is calculated via Sum of Absolute Differences between both image frames. SAD measures the distortion between two frames by evaluating the similarity between image blocks. On the cornerstone of SAD values, affine transform is obtained which makes the inliers from the initial set of points to match with the inliers from the following set. It is clear from simulation results, inliers correspondences gets exactly coincident which gives more favorable results. The cores of the images are generally well aligned. Thus by utilizing the Random Sample Consensus (RANSAC) algorithm, a robust estimate of transformation is obtained.
Uploads
Papers by shamsundar kulkarni