FPGA-based object detection processor with HOG feature and SVM classifier

An，Fengwei1; Xu，Peng1; Xiao，Zhihua1; Wang，Chao2

10.1109/SOCC46988.2019.1570558044

2019-09-01

2164-1676

2164-1706

978-1-7281-3484-0

International System on Chip Conference

2019-September

187-190

3-6 Sept. 2019

Singapore

Computer vision is an important sensing technique to translate the information to decisions. In robotic applications, object detection is a critical skill to perform tasks for robots in complex environments. The deep-learning framework, e.g. You Only Look Once (YOLO), attracts much more attention recently. Moreover, it is not an optimal solution for a mobile robot since it requires a large scale of hardware resources, on-chip SRAMs, and power consumption. In this work, we report an object detection processor synchronizing the image sensor in FPGA with a cellbased histogram of oriented gradient (HOG) feature descriptor and support vector machine (SVM) classifier by parallel sliding window mechanism. The HOG feature extraction circuitry with pixel-based pipelined architecture constructs the cell-based feature vectors for parallelizing partial SVM-based classification in multiple sliding windows. The SVM classification produces the final result after accumulating the vector components in one sliding window. This framework can be used to both localize and recognize multiple objects in video footage. The proposed object processor, in which the SVM classifier is trained by INRIA datasets, is implemented and verified on Intel Stratix IV FPGA for the pedestrian.

Computer vision histogram of oriented gradient (HOG) object detection processor support vector machine (SVM)

第一

英语

EI

20202208711542

Classification (of information) ; Deep learning ; Support vector machines ; Decoding ; Feature extraction ; Field programmable gate arrays (FPGA) ; Graphic methods ; Computer vision ; Vectors ; Object recognition

Ergonomics and Human Factors Engineering:461.4 ; Information Theory and Signal Processing:716.1 ; Logic Elements:721.2 ; Computer Software, Data Handling and Applications:723 ; Data Processing and Image Processing:723.2 ; Computer Applications:723.5 ; Vision:741.2 ; Information Sources and Analysis:903.1 ; Algebra:921.1

2-s2.0-85085189285

Scopus

1.Southern University of Science and Technology,China
2.Huazhong University of Science and Technology,China

An，Fengwei,Xu，Peng,Xiao，Zhihua,et al. FPGA-based object detection processor with HOG feature and SVM classifier[C],2019:187-190.