Embedded Optimization Technology of Sgemv Algorithm for Image Retrieval
Pedestrian re-identification mainly solves the recognition and retrieval of pedestrians in cross-camera and cross-scene situations.It is another visual task for"people"after face recognition.The main task is to find the same person for a specific pedestrian in a large-scale image collection input by multiple cameras.How to quickly retrieve specific pedestrians from a large number of pedestrian databases at the edge near the camera is an important issue in pedestrian re-identification research.Due to the limited computing power of the embedded platform at the edge,this paper proposes an image retrieval-oriented sgemv algorithm embedding In the edge end,the sgemv algorithm is accelerated and optimized using tech-nologies such as loop unrolling,OpenMP,and Neon,and the experimental verification is carried out on the Phytium D2000 embedded platform and the Galaxy Kirin system.The results show that,the speed after optimization is 5.2 times higher than that before optimization.This method effectively improves the effi-ciency of image retrieval at the edge end.
万方数据
维普
