Tracking by Detection of Multiple Faces using SSD and CNN Features

• 발행기관: 한국스마트미디어학회
• 저자명: Do Nhu Tai Soo-Hyung Kim Guee-Sang Lee Hyung-Jeong Yang In-Seop Na A-Ran Oh
• 간행물 정보: 『스마트미디어저널』Vol7, No.4, 53~61쪽, 전체 9쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2018.12.31

영문 초록

Multi-tracking of general objects and specific faces is an important topic in the field of computer vision applicable to many branches of industry such as biometrics, security, etc. The rapid development of deep neural networks has resulted in a dramatic improvement in face recognition and object detection problems, which helps improve the multiple-face tracking techniques exploiting the tracking-by-detection method. Our proposed method uses face detection trained with a head dataset to resolve the face deformation problem in the tracking process. Further, we use robust face features extracted from the deep face recognition network to match the tracklets with tracking faces using Hungarian matching method. We achieved promising results regarding the usage of deep face features and head detection in a face tracking benchmark.

목차

Ⅰ. INTRODUCTION

Ⅱ. PROPOSED FACE DETECTION ALGORITHM

Ⅲ. DATA ASSOCIATION

Ⅳ. EXPERIMENTAL RESULTS

Ⅴ. CONCLUSION

키워드

Image Processing Human face tracking Active Appearance Model