| Summary: | 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
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