Abstract
Key issues in bridging the semantic gap for content analysis of video include flexibility required from the software, real time implementation and cost effectiveness. In recent years industry has begun to take a more realistic view of what to expect from video content analysis systems in the near future. This chapter presents the state-of-the-art trends in semantic video analysis in industry. The key challenges in bridging the semantic gap are discussed. It also presents the research trends in video analytics. © 2011 Springer-Verlag Berlin Heidelberg.
| Original language | English |
|---|---|
| Title of host publication | Studies in Computational Intelligence|Stud. Comput. Intell. |
| Subtitle of host publication | Studies in Computational Intelligence |
| Place of Publication | Berlin |
| Publisher | Springer Nature |
| Pages | 443-457 |
| Number of pages | 14 |
| Volume | 346 |
| Publication status | Published - 2011 |
Keywords
- analytics
- challenges
- issues
- Semantic
- semantic-gap
- trends
- understanding
- video