Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey
Kun Shi, Shibo He, Zhenyu Shi, Chen An-jun, Zehui Xiong, Jiming Chen, Jun Luo
Nanyang Technological University State Key Laboratory of Industrial Control Technology Singapore University of Technology and Design
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Multi-modal fusion is imperative to the implementation of reliable object detection and tracking in complex environments. Exploiting the synergy of heterogeneous modal information endows perception systems the ability to achieve more comprehensive, robust, and accurate performance. As a nucleus concern in wireless-vision collaboration, radar-camera fusion has prompted prospective research directions owing to its extensive applicability, complementarity, and compatibility. Nonetheless, there still lacks a systematic survey specifically focusing on deep fusion of radar and camera for object detection and tracking. To fill this void, we embark on an endeavor to comprehensively review radar-camera fusion in a holistic way. First, we elaborate on the fundamental principles, methodologies, and applications of radar-camera fusion perception. Next, we delve into the key techniques concerning sensor calibration, modal representation, data alignment, and fusion operation. Furthermore, we provide a detailed taxonomy covering the research topics related to object detection and tracking in the context of radar and camera technologies. Finally, we discuss the emerging perspectives in the field of radar-camera fusion perception and highlight the potential areas for future research.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
工程Infrared Target Detection Methodologies
参考文献 378
此处列出前 3 条
引用本文 30
按被引量排序,此处列出前 3 条