Visual-Centric Algorithm and Architecture Design of Video Stabilization

• Main Authors: Keng-Yen Huang, 黃耿彥
• Other Authors: 陳良基
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/39155688527904545829

碩士 === 國立臺灣大學 === 電子工程學研究所 === 99 === This thesis is to investigate the need for solving the problem of shaky video stream. The way we try to stabilize the video is also known as the video sta- bilization system. This stabilization system is for removing the unwanted oscillation while conserving the intentional camera motion. In the past, people tend to resort to he help of some devices like tripod to reduce the negative eRects induced by unstable camera platforms. However, with the development of camera image retrieving technology, camera sensors are be- coming more and more small that we have to think other ways to stabilize the annoying video stream. By the assistance of computer vision technique, there is information that we can learn directly from the video itself. Thus, various computer vision based approaches have been brought up to com- pensate the uncomfortable video sequence. Unfortunately, these computer vision based approaches often require longer processing time to guarantee a certain quality. As a result, many algorithms are utilized in post processing stage to reexamine the shaky video and reconstruct a new stabilized result. But there is more need for a real-time system that can provide a smooth video result. An e±cient video stabilization system which is targeted at real-time applications is revealed in this thesis. For various applications or further image processing techniques, performance can be largely enhanced if pro- vided with a video in high quality. In order to achieve this goal, we develop a visual-centric video stabilization algorithm. The core idea is to provide a real-time stabilization technique for applications, thus, we propose a high e±ciency video stabilization system with the following special characteris- tics. The ¯rst and the main idea is that we should put more emphasis on the information that we really care about. Visual ¯xation is thus adopted in our system. Each extracted feature is weighted diRerently based on its visual importance and reliability. In order to achieve real-time processing target, high e±ciency feature matching engine is constructed in our system. Locality sensitive hashing helps us to realize the feature matching procedure in hardware implementation. By applying the proposed bucket memory re- ducing scheme, the memory consumption of locality sensitive hashing is reduced by more than 90% compared with allocating full size of hash ta- bles. For insu±cient throughput, we adopt a 2 way set-associative cache to reduce the frequency of accessing outer feature memory. More than 50% of feature bus burden has been released. Through our proposed locality sen- sitive hashing scheme, we make it possible for the digital signal processing based real-time video stabilization system. The experimental results show our improvement and robust performance under diRerent conditions. The proposed video stabilization system is realized on a chip with 3￡ 3 in area using UMC 90nm technology. Average 202 frames per second of processing time is achieved