Abstract
In this study, the novel approach of real-time video stabilization system using a high-frame-rate (HFR) jitter sensing device is demonstrated to realize the computationally efficient technique of digital video stabilization for high-resolution image sequences. This system consists of a high-speed camera to extract and track feature points in gray-level 512times 496 image sequences at 1000 fps and a high-resolution CMOS camera to capture 2048times 2048 image sequences considering their hybridization to achieve real-time stabilization. The high-speed camera functions as a real-time HFR jitter sensing device to measure an apparent jitter movement of the system by considering two ways of computational acceleration; (1) feature point extraction with a parallel processing circuit module of the Harris corner detection and (2) corresponding hundreds of feature points at the current frame to those in the neighbor ranges at the previous frame on the assumption of small frame-to-frame displacement in high-speed vision. The proposed hybrid-camera system can digitally stabilize the 2048times 2048 images captured with the high-resolution CMOS camera by compensating the sensed jitter-displacement in real time for displaying to human eyes on a computer display. The experiments were conducted to demonstrate the effectiveness of hybrid-camera-based digital video stabilization such as (a) verification when the hybrid-camera system in the pan direction in front of a checkered pattern, (b) stabilization in video shooting a photographic pattern when the system moved with a mixed-displacement motion of jitter and constant low-velocity in the pan direction, and (c) stabilization in video shooting a real-world outdoor scene when an operator holding hand-held hybrid-camera module while walking on the stairs.
Highlights
Image stabilization [1,2,3,4,5] is a well-known process used to reduce undesired motion in image sequences which occur due to shaking or jiggling of a camera or rapidly moving objects while rolling the shutter
We developed a hybrid-camera system for real-time highresolution video stabilization that can simultaneously stabilize 2048 × 2048 images captured at 80 fps by executing frame-by-frame feature point tracking in real time at 1000 fps on a 512 × 512 HFR vision system
Photographic pattern we evaluated the video stabilization performance by observing a printed photographic pattern when the hybrid-camera system moved with drifting at a certain frequency in the pan direction
Summary
Image stabilization [1,2,3,4,5] is a well-known process used to reduce undesired motion in image sequences which occur due to shaking or jiggling of a camera or rapidly moving objects while rolling the shutter. The residual fluctuated motion in images can be reduced using various image processing techniques to estimate the local motion vectors, such as block matching [20,21,22,23], bit-plane matching [24, 25], Kalman-filter-based prediction [26,27,28,29,30], DFT filtering [31], particle filter [32], scale-invariant feature [33, 34], feature point matching [35,36,37,38,39], and optical flow estimation [40,41,42,43,44,45] These systems do not require any additional mechanism or optical device for video stabilization, and they have been used as low-cost video stabilizers in various applications such as airborne shooting [46,47,48,49,50,51,52], off-road vehicles [53], and teleoperated applications [54,55,56,57], including commercial applications [58,59,60,61,62]. Researchers have been reporting various approaches to achieve real-time DIS systems [63,64,65,66,67,68,69] for stabilizing a video sequence with simultaneous video processing at conventional frame rate, whereas most of them have limited ability to reduce large and quick apparent motion observed in images due to heavy computation in the frame corresponding process
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