19 June 2017 Heterogeneous computing for a real-time pig monitoring system
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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
Abstract
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.
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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
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KEYWORDS
Sensors

Computing systems

Parallel processing

Video

Video acceleration

Telecommunications

Video surveillance

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