Name
Title | ||
|---|---|---|
Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis. |
Abstract | ||
|---|---|---|
This paper presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly an... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCSI.2017.2758379 | IEEE Transactions on Circuits and Systems I: Regular Papers |
Keywords | Field | DocType |
Cameras,Surveillance,Algorithm design and analysis,Video sequences,Anomaly detection,Synchronization,Robustness | Computer vision,Anomaly detection,Object detection,External Data Representation,Subspace topology,Sparse approximation,Robustness (computer science),Linear subspace,Electronic engineering,Artificial intelligence,Mathematics,Computational complexity theory | Journal |
Volume | Issue | ISSN |
65 | 3 | 1549-8328 |
Citations | PageRank | References |
2 | 0.39 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas A. Thomaz | 1 | 11 | 3.59 |
| Eric Jardim | 2 | 7 | 1.93 |
| Allan F. da Silva | 3 | 9 | 2.22 |
| Eduardo A. B. da Silva | 4 | 238 | 46.50 |
| Sergio L. Netto | 5 | 141 | 26.27 |
| Hamid Krim | 6 | 520 | 59.69 |