Design and Implementation of Hardware-SVM-based Shot Detection System
Date Issued
2007
Date
2007
Author(s)
Hsu, Fu-Chun
DOI
en-US
Abstract
Structural analysis of video is an essential step to automatic video content
analysis. In a general video structure, shot is the most basic unit, and it must
be determined before any multimedia content-based retrieval applications.
However, despite the rich research efforts in software shot detection system,
there is a lack of shot detection system that is designed in hardware. In
this thesis, we proposed a shot boundary detection system using hardwarebased
Support-Vector-Machine(SVM). Our system can detect both cut shots
and gradual shots. We optimized the feature extraction process based on
global color histogram with a pipelined architecture to save memory and
increase the overall speed. The class imbalance problem in shot detection is
solved by using random pseudo-sampling at the SVM training stage. The
digital hardware SVM is designed using a fully-parallel pipelined architecture
and is highly configurable on vector dimensions. Our data wordlength only
used 4 bits signed integer plus one bit decimal in fixed number, while the
detection accuracy is competitive comparing with floating point software.
Our SVM classifier presented here can run a speed up to 251.62MHZ on
Xilinx Virtex IV XC4VSX35 FPGA, and the video processing on our shot
detection system can achieve 128 fps on PC. That makes our system met the
real-time constraints, and detect shots in a continous video stream such as
live-TV news or sports game.
Subjects
支援向量機
硬體
影片分段偵測
Support Vector Machine
hardware
shot boundary detection
Type
thesis
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