Real-Time Object Detection for Multi-Camera on Heterogeneous Parallel Processing Systems

In recent years, the need for object detection has significantly increased for multi-camera systems. However, the detection methods in such systems incur high computational cost, which leads to a major challenge in real-time applications. In this work, we propose a Scissor Algorithm for object detection using a multi-core CPU and a graphic processing unit (GPU). Leveraging the features of both the CPU and the GPU, the object detection method was enhanced in two stages: (a) pixel-to-pixel color filtering and (b) grouping. The proposed algorithm can effectively shrink the search area for detection and further improve the process of detection, thus effectively increasing the frame rate for real-time applications. Experimental results demonstrate the real-time performance of the proposed algorithm.