19 June 2017 Heterogeneous computing for a real-time pig monitoring system
Author Affiliations +
Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104431O (2017); doi: 10.1117/12.2280236
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore
Video sensor data has been widely used in automatic surveillance applications. In this study, we present a method that automatically detects pigs in a pig room by using depth information obtained from a Kinect sensor. For a real-time implementation, we propose a means of reducing the execution time by applying parallel processing techniques. In general, most parallel processing techniques have been used to parallelize a specific task. In this study, we consider parallelization of an entire system that consists of several tasks. By applying a scheduling strategy to identify a computing device for each task and implementing it with OpenCL, we can reduce the total execution time efficiently. Experimental results reveal that the proposed method can automatically detect pigs using a CPU-GPU hybrid system in real time, regardless of the relative performance between the CPU and GPU.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Younchang Choi, Jinseong Kim, Jaehak Kim, Yeonwoo Chung, Yongwha Chung, Daihee Park, Hakjae Kim, "Heterogeneous computing for a real-time pig monitoring system", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104431O (19 June 2017); doi: 10.1117/12.2280236; http://dx.doi.org/10.1117/12.2280236


Computing systems

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