Automated Whiteboard Lecture Video Summarization by Content Region Detection and Representation

2021 ◽  
Author(s):  
Bhargava Urala Kota ◽  
Alexander Stone ◽  
Kenny Davila ◽  
Srirangaraj Setlur ◽  
Venu Govindaraju
Keyword(s):  
Video Summarization ◽  
Region Detection ◽  
Lecture Video

Movie Video Summarization- Generating Personalized Summaries Using Spatiotemporal Salient Region Detection

2019 ◽  
Vol 10 (3) ◽  
pp. 1-26
Author(s):  
Rajkumar Kannan ◽  
Sridhar Swaminathan ◽  
Gheorghita Ghinea ◽  
Frederic Andres ◽  
Kalaiarasi Sonai Muthu Anbananthen
Keyword(s):  
Optical Flow ◽  
Video Summarization ◽  
Video Frame ◽  
Color Contrast ◽  
Color Distribution ◽  
Salient Region Detection ◽  
Salient Region ◽  
Region Detection ◽  
Video Summary ◽  
Salient Regions

Video summarization condenses a video by extracting its informative and interesting segments. In this article, a novel video summarization approach is proposed based on spatiotemporal salient region detection. The proposed approach first segments a video into a set of shots which are ranked with spatiotemporal saliency scores. The score for a shot is computed by aggregating the frame level spatiotemporal saliency scores. This approach detects spatial and temporal salient regions separately using different saliency theories related to objects present in a visual scenario. The spatial saliency of a video frame is computed using color contrast and color distribution estimations and center prior integration. The temporal saliency of a video frame is estimated as an integration of local and global temporal saliencies computed using patch level optical flow abstractions. Finally, top ranked shots with the highest saliency scores are selected for generating the video summary. The objective and subjective experimental results demonstrate the efficacy of the proposed approach.

Content-Based Music Summarization and Classification

2011 ◽  
pp. 99-134
Author(s):  
Changsheng Xu ◽  
Xi Shao ◽  
Namunu C. Maddage ◽  
Jesse S. Jin ◽  
Qi Tian
Keyword(s):  
Video Summarization ◽  
Current Status ◽  
Future Research ◽  
Practical Applications ◽  
Region Detection ◽  
Genre Classification ◽  
Full Picture ◽  
Comprehensive Survey ◽  
Music Signals ◽  
Music Genre Classification

This chapter aims to provide a comprehensive survey of the technical achievements in the area of content-based music summarization and classification and to present our recent achievements. In order to give a full picture of the current status, the chapter covers the aspects of music summarization in compressed domain and uncompressed domain, music video summarization, music genre classification, and semantic region detection in acoustical music signals. By reviewing the current technologies and the demands from practical applications in music summarization and classification, the chapter identifies the directions for future research.

Robust handwriting extraction and lecture video summarization

2016 ◽  
Vol 76 (5) ◽  
pp. 7067-7085 ◽  
Author(s):  
Greg C. Lee ◽  
Fu-Hao Yeh ◽  
Ying-Ju Chen ◽  
Tao-Ku Chang
Keyword(s):  
Video Summarization ◽  
Lecture Video

Improving the Computational Cost for Copied Region Detection in Forensic Images

2016 ◽  
Vol 2 (1) ◽  
pp. 55
Author(s):  
Tu Huynh-Kha ◽  
Thuong Le-Tien ◽  
Synh Ha ◽  
Khoa Huynh-Van
Keyword(s):  
Wavelet Transform ◽  
Euclidean Distance ◽  
Research Work ◽  
Computational Cost ◽  
Correlation Coefficients ◽  
Zernike Moments ◽  
Computational Time ◽  
Discrete Wavelet ◽  
Feature Vectors ◽  
Region Detection

This research work develops a new method to detect the forgery in image by combining the Wavelet transform and modified Zernike Moments (MZMs) in which the features are defined from more pixels than in traditional Zernike Moments. The tested image is firstly converted to grayscale and applied one level Discrete Wavelet Transform (DWT) to reduce the size of image by a half in both sides. The approximation sub-band (LL), which is used for processing, is then divided into overlapping blocks and modified Zernike moments are calculated in each block as feature vectors. More pixels are considered, more sufficient features are extracted. Lexicographical sorting and correlation coefficients computation on feature vectors are next steps to find the similar blocks. The purpose of applying DWT to reduce the dimension of the image before using Zernike moments with updated coefficients is to improve the computational time and increase exactness in detection. Copied or duplicated parts will be detected as traces of copy-move forgery manipulation based on a threshold of correlation coefficients and confirmed exactly from the constraint of Euclidean distance. Comparisons results between proposed method and related ones prove the feasibility and efficiency of the proposed algorithm.

Video Summarization by Curve Simplification

1998 ◽  
Author(s):  
Daniel DeMenthon ◽  
Vikrant Kobla ◽  
David Doermann
Keyword(s):  
Video Summarization ◽  
Curve Simplification

Image Stitching Algorithms - A Review

2016 ◽  
Vol 1 (2) ◽  
pp. 14-18
Author(s):  
Srishty Suman ◽  
Utkarsh Rastogi ◽  
Rajat Tiwari
Keyword(s):  
Video Compression ◽  
Video Summarization ◽  
Video Stabilization ◽  
Image Stitching

Image stitching is the process of combining two or more images of the same scene as a single larger image. Image stitching is needed in many applications like video stabilization, video summarization, video compression, panorama creation. The effectiveness of image stitching depends on the overlap removal, matching of the intensity of images, the techniques used for blending the image. In this paper, the various techniques devised earlier for the image stitching and their applications in the relative places has been reviewed.

Efficient 3D mesh salient region detection using local homogeneity measure

2018 ◽  
Vol 12 (9) ◽  
pp. 1663-1672 ◽  
Author(s):  
Abdul Rahman El Sayed ◽  
Abdallah El Chakik ◽  
Hassan Alabboud ◽  
Adnan Yassine
Keyword(s):  
Salient Region Detection ◽  
3D Mesh ◽  
Local Homogeneity ◽  
Salient Region ◽  
Region Detection
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