TAILIEUCHUNG - Towards a high performance and causal stabilization system for video captured from moving camera

In this paper, we propose a novel software-based system to stabilize camera videos in real-time by combining several general models. The main contribution of proposed system is the capability of processing instantaneously video achieved from moving devices to meet quality requirements by using Harris with Optical-flow, and Lucas-Kanade methods for motion estimation. | Journal of Science & Technology 128 (2018) 048-054 Towards A High-Performance and Causal Stabilization System for Video Captured from Moving Camera Vu Nguyen Giap, Nguyen Binh Minh * Hanoi University of Science and Technology - No. 1, Dai Co Viet, Hai Ba Trung, Hanoi, Vietnam Received: March 05, 2018; Accepted: June 29, 2018 Abstract Video shot from camera attached to moving devices like smartphone, and drone are often shaken because unwanted movements of the image sensors, which are caused by unstable motions of the devices during their operation (. moving, fly). This phenomenon impacts on effectiveness of systems that use camera videos as input data such as security surveillance and object tracking. In this paper, we propose a novel software-based system to stabilize camera videos in real-time by combining several general models. The main contribution of proposed system is the capability of processing instantaneously video achieved from moving devices to meet quality requirements by using Harris with Optical-flow, and Lucas-Kanade methods for motion estimation. We also propose several mechanisms including frame partition and matching for corner detector when applying Harris method to ensure processing quality and system performance. In our system, we also use Kalman filter for prediction model of motion compensation. Our experiments proved that the average processing speed of our system can reach 35 fps, which satisfies the real-time requirement. Keywords: Causal system, motion prediction, performance, real-time, video stabilization. 1. Introduction* techniques to improve performance in stabilizing streaming videos in real-time. There are two conditions for the real-time meaning here. First, the proposed system response time should be almost instantaneous in comparison with actual captured video from camera. Second, the processing system must be causal. In other word, the current frame stabilization uses only data obtained from this frame and previous .

• Điện - Điện tử
• Causal system
• Motion prediction
• Real time
• Video stabilization
• Lucas Kanade methods