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| 6,831,677 | System and method for facilitating the adjustment of disparity in a stereoscopic panoramic image pair. |
| 6,795,109 | Stereo panoramic camera arrangements for recording panoramic images useful in a stereo panoramic image pair. |
| 6,665,003 | System and method for generating and displaying panoramic images and movies. |
Jitter Camera:
The resolution of videos can be computationally enhanced by moving the camera and applying super-resolution algorithms.
However, a moving camera introduces motion blur, which limits the quality of super-resolution.
To overcome this limitation, we have developed a novel camera called the "jitter camera".
The jitter camera produces shifts between consecutive video frames without introducing any motion blur.
This is done by shifting the video detector instantaneously and timing the shifts to occur between pixel integration periods.
The videos captured by the jitter camera are processed by an adaptive super-resolution algorithm that handles complex dynamic
scenes in a robust manner producing a video that has a higher resolution than the captured one.
(With Assaf Zomet and Shree K. Nayar).
[Project Page]
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Motion Deblurring:
Motion blur due to camera motion can significantly degrade the quality of an image.
Since the path of the camera motion can be arbitrary, deblurring of motion blurred images is a hard problem.
In this project, we exploit the fundamental trade-off between spatial resolution and temporal resolution to construct
a hybrid camera that can measure its own motion during image integration.
The acquired motion information is used to compute a point spread function (PSF) that represents the path of the camera during integration.
This PSF is then used to deblur the image.
This prototype system was evaluated in different indoor and outdoor scenes using long exposures and complex camera motion paths.
The results show that, with minimal resources, hybrid imaging outperforms previous approaches to the motion blur problem.
(With Shree K. Nayar).
[Project Page]
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Motion and Transparent Objects:
The perception of transparent objects from images is known to be a very hard vision problem.
Given a single image, it is difficult to even detect the presence of transparent objects in the scene.
In this project, we explore what can be said about transparent objects by a moving observer.
We show how features that are imaged through a transparent object behave differently from those that are rigidly attached to the scene.
We present a novel model-based approach to recover the shapes and the poses of transparent objects from known motion.
The objects can be complex in that they may be composed of multiple layers with different refractive indices.
We have applied our algorithm to real scenes that include transparent objects and recovered the shapes and dimensions of the objects with high accuracy.
(With Shree K. Nayar).
[Project Page]
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Segmentation with Invisible Keying Signal:
Chroma keying is the process of segmenting objects from images and video using color cues. i
A blue (or green) screen placed behind an object during recording is used in special effects and in virtual studios.
A different background later replaces the blue color. A new method for automatic keying using invisible signal is presented.
The advantages of the new approach over conventional chroma keying are unlimited color range for foreground objects
and no foreground contamination by background color.
The method can be used in real-time and no user assistance is required.
A new camera design and a single chip sensor design for keying are also presented.
[Project Page]
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Omnidirectional Stereo Imaging:
An Omnistereo panorama consists of a pair of panoramic images, where one panorama is for the left eye and another
panorama is for the right eye. The panoramic stereo pair provides a stereo sensation up to a full 360 degrees. Omnistereo panoramas
cannot be photographed by two omnidirectional cameras from two viewpoints, but can be constructed by mosaicing together images
from a single rotating camera. Capturing panoramic omnistereo images with a rotating camera makes it impossible to capture dynamic
scenes at video rates and limits omnistereo imaging to stationary scenes. We, therefore, present two possibilities for capturing
omnistereo panoramas using optics without any moving parts. A special mirror is introduced such that viewing the scene through this
mirror creates the same rays as those used with the rotating cameras. A lens for omnistereo panorama is also introduced.
Omnistereo panoramas can also be rendered by computer graphics methods to represent virtual environments.
(With Shmuel Peleg and
Yael Pritch).
[Project Page]
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Robust Motion and Pose Estimation using Linear Programming:
Motion Estimation in real time from point-to-line correspondences using
linear programming is presented. Point-to-line correspondences are the most reliable measurements
for image motion given the aperture effect, and it is shown how they can approximate other motion measurements
as well. An error measure for image alignment using the L1 metric and based on point-to-line correspondences
achieves results which are more robust than those for the commonly used L2 metric. The L1 error measure
is minimized using linear programming.
The entire computation is performed in real-time on a PC (Pentium MMX 300Mhz) without special hardware.
(With Shmuel Peleg and
Michael Werman).
[Project Page]
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