Topic-based Video Analysis: A Survey
| Autor: | Dilip K. Prasad, Ratnabali Pal, Arif Ahmed Sekh, Samarjit Kar, Debi Prosad Dogra, Partha Pratim Roy |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Topic model
Scene analysis Information retrieval General Computer Science Scope (project management) Computer science Supervised learning Perspective (graphical) Information processing ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Motion (physics) Theoretical Computer Science 020204 information systems 0202 electrical engineering electronic engineering information engineering Unsupervised learning 020201 artificial intelligence & image processing |
| Popis: | © Author | ACM 2021. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Computing Surveys, https://doi.org/10.1145/3459089. Manual processing of a large volume of video data captured through closed-circuit television is challenging due to various reasons. First, manual analysis is highly time-consuming. Moreover, as surveillance videos are recorded in dynamic conditions such as in the presence of camera motion, varying illumination, or occlusion, conventional supervised learning may not work always. Thus, computer vision-based automatic surveillance scene analysis is carried out in unsupervised ways. Topic modelling is one of the emerging fields used in unsupervised information processing. Topic modelling is used in text analysis, computer vision applications, and other areas involving spatio-temporal data. In this article, we discuss the scope, variations, and applications of topic modelling, particularly focusing on surveillance video analysis. We have provided a methodological survey on existing topic models, their features, underlying representations, characterization, and applications in visual surveillance’s perspective. Important research papers related to topic modelling in visual surveillance have been summarized and critically analyzed in this article. |
| Databáze: | OpenAIRE |
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