Andrew Joseph Crawford

Gradient based dominant motion estimation with integral projections for real time video stabilisation

This paper presents a new expression of the relationship between integral projections and motion in an image pair. The resulting new multiresolution gradient based approach is used to estimate dominant motion in image sequences degraded by random shake. The paper also describes an implementation using the GPU as a coprocessor for the CPU that allows, for the first time, real time video stabilisation in software on broadcast standard definition television images.

Semi-transparent blotches removal from sepia images exploiting visibility laws

This paper presents a novel model for the removal of semi-transparent blotches on the digitized copy of sepia archive photographs. As these defects cannot be successfully eliminated by conventional interpolation methods, a proper combination of a novel visual distortion and multiresolution analysis is used for performing user-independent detection and restoration. Extensive experimental results and comparative studies show the potential of the proposed model in terms of visual quality and computational complexity.

Temporal synchronization of multiple audio signals

Given the proliferation of consumer media recording devices, events often give rise to a large number of recordings. These recordings are taken from different spatial positions and do not have reliable timestamp information. In this paper, we present two robust graph-based approaches for synchronizing multiple audio signals. The graphs are constructed atop the over-determined system resulting from pairwise signal comparison using cross-correlation of audio features. The first approach uses a Minimum Spanning Tree (MST) technique, while the second uses Belief Propagation (BP) to solve the system. Both approaches can provide excellent solutions and robustness to pairwise outliers, however the MST approach is much less complex than BP. In addition, an experimental comparison of audio features-based synchronization shows that spectral flatness outperforms the zero-crossing rate and signal energy.

Multi-Scale Semi-Transparent Blotch Removal on Archived Photographs using Bayesian Matting Techniques and Visibility Laws

This paper presents an automatic technique to remove semi-transparent blotches (due to moisture) from archived photographs and documents. Blotches are processed in the HSV space. While chroma components are processed using a simple texture synthesis method, the intensity component is split into an over-complete wavelet representation. In the approximation band, the blotch is modelled as an alpha matte which reduces the intensity of the image in a non-uniform yet smooth manner. The alpha matte is estimated using a Bayesian approach and its effect reversed. Wavelet details are left unchanged in the case of perfect semi-transparency or attenuated using visibility laws whenever dirt and dust cause spurious edges. Experimental results achieved on many historical photographs show the effectiveness of the proposed approach.

Content based access for a massive database of human observation video

We present in this paper a CBIR system for use in a psychological study of the relationship between human movement and Dyslexia. The system allows access to up to 500 hours of video and is an example of a scientific user context. This user context requires 100% accurate indexing and retrieval for a set of specific queries. This paper presents a novel use of interactive visual and audio cues for attaining this level of indexing performance. Furthermore, the issue of motion estimation accuracy in the presence of compression artifacts is explored as part of the data integrity storage problem. In addition, content based motion analysis techniques accurate enough to parse sequences on the basis of motion and objectively evaluate that motion are investigated. The tool allows Psychologists to undertake a study that would previously be impractical and the paper presents a number of lessons gained from the ongoing work

Measuring noise correlation for improved video denoising

The vast majority of previous work in noise reduction for visual media has assumed uncorrelated, white, noise sources. In practice this is almost always violated by real media. Film grain noise is never white, and this paper highlights that the same applies to almost all consumer video content. We therefore present an algorithm for measuring the spatial and temporal spectral density of noise in archived video content, be it consumer digital camera or film orginated. As an example of how this information can be used for video denoising, the spectral density is then used for spatio-temporal noise reduction in the Fourier frequency domain. Results show improved performance for noise reduction in an easily pipelined system.

Perception measures for digital restoration of semi-transparent blotches

This paper presents a novel model for the restoration of semitransparent blotches. It is based on two perception measures that describe a complicated object, like a semi-transparent blotch, on a complicated background, like textures in real-world images. Experimental results on archive photographs show that the proposed approach is able to achieve good results with a low computational effort and in a completely automatic way.

Digital removal of blotches with variable semi-transparency using visibility laws

This paper presents an automatic technique that removes blotches from archived photographs. In particular, we focus on blotches caused by water and dirt that cause a variable semi-transparency in the degraded region. The proposed digital removal consists of an automatic shrinking of the blotch that preserves the original image details. This operation is based on visibility laws in the wavelet domain. Preliminary experimental results show that the proposed model is also effective on critical blotches produced by dust and dirt.