System identification: theory for the user
System identification: theory for the user
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Performance of optical flow techniques
International Journal of Computer Vision
Digital Control Systems
Digital Image Restoration
Digital Image Restoration
Unsmearing Visual Motion: Development of Long-Range Horizontal Intrinsic Connections
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Depth from Defocus vs. Stereo: How Different Really Are They?
International Journal of Computer Vision - Special issue on computer vision research at the Technion
Motion-Based Motion Deblurring
IEEE Transactions on Pattern Analysis and Machine Intelligence
A biologically inspired method for estimating 2D high-speed translational motion
Pattern Recognition Letters
Measurement of sinusoidal vibration from motion blurred images
Pattern Recognition Letters
Vehicle speed detection from a single motion blurred image
Image and Vision Computing
Invertible motion blur in video
ACM SIGGRAPH 2009 papers
ACM SIGGRAPH Asia 2009 papers
On the Apparent Transparency of a Motion Blurred Object
International Journal of Computer Vision
Estimation of rotation parameters from blurred image
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Two algorithms for motion estimation from alternate exposure images
Proceedings of the 2010 international conference on Video Processing and Computational Video
Kernel estimation from salient structure for robust motion deblurring
Image Communication
Improved image deblurring based on salient-region segmentation
Image Communication
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Motion smear is an important visual cue for motion perception by the human vision system (HVS). However, in image analysis research, exploiting motion smear has been largely ignored. Rather, motion smear is usually considered as a degradation of images that needs to be removed. In this paper, we establish a computational model that estimates image motion from motion smear information驴"motion from smear." In many real situations, the shutter of the sensing camera must be kept open long enough to produce images of adequate signal-to-noise ratio (SNR), resulting in significant motion smear in images. We present a new motion blur model and an algorithm that enables unique estimation of image motion. A prototype sensor system that exploits the new motion blur model has been built to acquire data for "motion-from-smear." Experimental results on images with both simulated smear and real smear, using our "motion-from-smear" algorithm as well as a conventional motion estimation technique, are provided. We also show that temporal aliasing does not affect "motion-from-smear" to the same degree as it does algorithms that use displacement as a cue. "Motion-from-smear" provides an additional tool for motion estimation and effectively complements the existing techniques when apparent motion smear is present.