Video Segmentation Based On Descriptors Extracted from Wavelet Transforms
Spatiotemporal representation learning and zero-shot learning using tensor factori...
An approach to semantic segmentation exploiting multimodality and temporal charact...
| Full text | |
| Author(s): |
Sousa e Santos, Anderson Carlos
;
Pedrini, Helio
;
IEEE
Total Authors: 3
|
| Document type: | Journal article |
| Source: | 2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC); v. N/A, p. 6-pg., 2017-01-01. |
| Abstract | |
Despite its associated challenges, the development of mechanisms for storing, indexing, transmitting and visualizing multimedia content is crucial in order to efficiently deal with the large amount of data generated by several different sources. Digital video technology has advanced rapidly, such that temporal video segmentation methods for automatically detecting transitions in video sequences play an important role in the content analysis tasks. In this work, we propose and evaluate a video shot boundary detection approach based on the Weber local descriptor. Experiments conducted on different datasets demonstrate the effectiveness of our method, whose results are compared against other approaches of the literature. (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |