Master of Electrical Engineering Program Cornell University Design Project Report Project Title: 2D to 3D Video Conversion with Static Scene and Horizontal Camera Motion Author: Ling-Wei Lee Abstract: Four automate methods to convert two-dimensional (2D) video to three-dimensional (3D) for video with only static scene and horizontal camera motion have been proposed in this project. Our approach...

Extracting moving objects from a video sequence is the first step of many video processing applications, including traffic monitoring and security surveillance. If the camera is fixed in the scene, we can detect moving objects by background subtraction, and many methods have been proposed for generating background images in varying illumination conditions[4, 13]. For images taken by a pan-tilt ...

Most algorithms in 3-D Computer Vision rely on the pinhole camera model because of its simplicity, whereas video optics, especially low-cost wide-angle lens, generate a lot of non-linear distortion which can be critical. To nd the distortion parameters of a camera, we use the following fundamental property: a camera follows the pinhole model if and only if the projection of every line in space ...

A computational methodology for reorienting, repositioning, and merging camera positions within a region under surveillance is proposed, so as to optimally cover all features of interest without overburdening human or machine analysts with an overabundance of video information. This streamlines many video monitoring applications, such as vehicular traffic and security camera monitoring, which a...

In this paper we propose a different approach based on a spatio-temporal feature called the Spatio Temporal Regularity Flow (SPREF) to stabilize unwanted camera motions in a video, recognize the camera motion patterns between consecutive frames and Group of Frames(GOF) and track the motion of an object in a video with the background subtracted. The method for stabilization based on Camera Motio...

This paper proposes a simple but yet an effective new method for the problem of digital video camera identification. It is known that after an exposure time of 0.15 seconds, the green channel is the noisiest of the three RGB colour channels [5]. Based on this observation, the digital camera pattern noise reference, which is extracted using only the green channel of the frames and is called Gree...

Computer scientists have made ceaseless efforts to replicate cognitive video understanding abilities of human brains onto autonomous vision systems. As video surveillance cameras become ubiquitous, there is a surge in studies on automated activity understanding and unusual event detection in surveillance videos. Nevertheless, video content analysis in public scenes remained a formidable challen...

This paper presents an optimization framework for estimating the motion and underlying physical parameters of a rigid body in free flight from video. The algorithm takes a video clip of a tumbling rigid body of known shape and generates a physical simulation of the object observed in the video clip. This solution is found by optimizing the simulation parameters to best match the motion observed...

This paper presents a scalable, discreet and mobile video-camera system that takes elevated video data of roadway locations for traffic safety analysis. The video is used to extract microscopic traffic parameters including road-user trajectories, lane changes and speeds. Collected video data is processed using an open-source automatic tracking tool. Trajectories can be then used to analyse road...

”We want to record our entire life by video” is the motivation of this research. Recently developing wearable devices and huge storage devices will make it possible to keep entire life by video. We could capture 70 years of our life, however, the problem is how to handle such a huge data. Automatic summarization based on personal interest should be required. In this paper we propose an approach...