A high speed feature matching architecture for real-time video stabilization
An efficient feature matching architecture targets at real-time video stabilization is revealed in this paper. For some applications, such as vehicular application, real-time video stabilization is needed to provide instant stable video input. However, feature matching is usually the bottleneck to achieve high performance. High speed feature matching architecture is proposed to accelerate the performance of video stabilization. Locality sensitive hashing (LSH) helps us realize the feature matching procedure in hardware implementation. By applying the proposed dynamic table allocation and on-chip cache mechanism, this work achieves 422K queries/s and real-time feature matching with 90% in memory reduction and more than 50% in relieving the feature bus burden of the system.