Name
Title | ||
|---|---|---|
Detection Of Abandoned Objects Using Robust Subspace Recovery With Intrinsic Video Alignment |
Abstract | ||
|---|---|---|
The detection of abandoned objects in videos from moving cameras is of great importance to automatic surveillance systems that monitor large and visually complex areas. This paper proposes a new method based on sparse decompositions to identify video anomalies associated with abandoned objects. The proposed scheme inherently incorporates synchronization between the reference (anomaly-free) and target (under analysis) sequences thus reducing the implementation complexity of the overall surveillance system. Results indicate that the proposed video-processing scheme can lead to 95% complexity reduction while maintaining excellent detection capability of foreground objects. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | Computer vision,Synchronization,Subspace topology,Computer science,Matrix decomposition,Reduction (complexity),Artificial intelligence,Instrumental and intrinsic value,Sparse matrix |
DocType | ISSN | Citations |
Conference | 0271-4302 | 0 |
PageRank | References | Authors |
0.34 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas A. Thomaz | 1 | 11 | 3.59 |
| Allan F. da Silva | 2 | 9 | 2.22 |
| Eduardo A. B. da Silva | 3 | 238 | 46.50 |
| Sergio L. Netto | 4 | 141 | 26.27 |
| Hamid Krim | 5 | 520 | 59.69 |