Dynamic Switching State Systems for Visual Tracking

• Tác giả: Stefan Becker
• Ngôn ngữ: eng
• Thông tin xuất bản: Karlsruhe : KIT Scientific Publishing, 2020
• Mô tả vật lý: 1 electronic resource (228 p.)
• Bộ sưu tập: Tài liệu truy cập mở
• ID: 207952
• Chủ đề: 1. Computer science

Tóm tắt

This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together.