FPGA Implementation of a CNN for Oriented Object Detection in Aerial Images

19/06/2024

The objective of this work is to design and implement a hardware/software system for oriented object detection of aerial images. The system is based on a convolutional neural network (CNN) detector and is aimed at processing one aerial image per second using a system-on-chip field-programmable gate array (SoC FPGA). Object detection in aerial images and videos is an important and challenging computer vision problem with important real-world applications such as emergency rescue, disaster relief, and surveillance. Oriented object detection considers both the position of the object and its rotation angle or orientation which makes detections significantly more accurate but more computationally intensive. Most target applications must be locally computed on unmanned aerial vehicles (UAVs), which requires implementing efficient solutions on edge devices, namely SoC FPGAs. The hardware/software system implements an optimized version of an oriented object detection model based on the YOLO object detection algorithm. The original YOLO model was optimized and quantized, with both weights and activations represented with a specific 8-bit fixed-point format, to provide an efficient hardware-friendly solution. The system is composed by a dedicated hardware accelerator, which accelerates the inference of the main layers of the CNN model by executing 256 multiply-accumulate operations in parallel, and by a software processor that executes the less computing intensive functions. The final hardware/software system, implemented in a Zynq SoC FPGA, executes the inference of the R-YOLOv4 with a frame rate close to 1 FPS and a power consumption of only 7.3 W.

Autores da comunidade :

• 

  F

  Francisco Miguel Correia Torcato Carrilho

  ist193062

Orientadores desta instituição:

• 

  M

  Mário Pereira Véstias

  ist402376

• 

  H

  Horácio Cláudio De Campos Neto

  ist11900

electrical-engineering-electronic-engineering-information-engineering - Engenharia Eletrotécnica, Eletrónica e Informática

eng - Inglês

Instituto Superior Técnico