Optimization of lateral interaction in accumulative computation on GPU-based platform
The lateral interaction in accumulative computation (LIAC) algorithm is a biologically inspired method that allows us to detect moving objects from image sequences acquired from fixed surveillance cameras. This method achieves excellent precision but requires a high processing time. Sequential imple...
| Authors: | , , , , |
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| Format: | article |
| Publication Date: | 2019 |
| Country: | España |
| Institution: | Universidad de Castilla-La Mancha |
| Repository: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/32909 |
| Online Access: | https://doi.org/10.1007/s11227-018-02736-y https://hdl.handle.net/10578/32909 |
| Access Level: | Open access |
| Keyword: | Acceleration GPU HPC Lateral interaction in accumulative computation Motion detection Optimization |
| Summary: | The lateral interaction in accumulative computation (LIAC) algorithm is a biologically inspired method that allows us to detect moving objects from image sequences acquired from fixed surveillance cameras. This method achieves excellent precision but requires a high processing time. Sequential implementation is too slow and cannot achieve real-time processing. In this paper, we present several improvements to the LIAC algorithm that increase its efficiency in terms of execution time and energy consumption. In particular, a GPU-based implementation delivers the same precision and is notably faster and more energy efficient than the sequential implementation. |
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