Motion estimation using complex wavelets

Magarey, J.; Kingsbury, Nick

doi:10.1109/icassp.1996.547759

Cited by 25 publications

(50 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other valuable contributions in the area of motion estimation and compensation techniques are due to, e.g., Magarey and Kingsbury at Cambridge University [153], Czerepinski and Bull at the University of Bristol [154], and Nieweglowski et al [155]. The error-resilient entropy coding (EREC) algorithm of Redmill and Kingsbury constitutes an important milestone toward improving the bit-error sensitivity of variable-length coded video [156], facilitating the employment of run-length coded standard MPEG-based [50] or H.263-based video communications.…”

Section: A Advances In Low-rate Video Compressionmentioning

confidence: 99%

Interactive cellular and cordless video telephony: State-of-the-art system design principles and expected performance

2000

View full text Add to dashboard Cite

Second-generation (2G) mobile radio standards have not been designed with video communications in mind, although the employment of error-resilient, constant-bit-rate proprietary video codecs over these systems is realistic. The third-generation (3G) systems I. STATE-OF-THE-ART SYSTEM COMPONENT DEVELOPMENTS A. Introduction and OutlineThe subject of mobile radio communications has reached a state of maturity over the past two decades, as indicated by the excellent monographs by Jakes This contribution attempts to summarize a range of recent advances in the field of bandwidth-efficient wireless video communications. In this section, we commence our discourse with a brief overview of the wireless scene and, in particular, by considering the video transmission capabilities of the existing and future wireless systems. The geographical variation of the cellular channel capacity is characterized by Section II, as a motivation for invoking burst-by-burst adaptive transceivers [27]- [29]. The nature of co-channel interference (CCI)-which is the most dominant channel impairment in wireless systems-is the topic of Section III, where it is shown that the geographic variation of CCI justifies the employment of multimode transceivers, which are discussed in Section IV. Low-rate video compression aspects are reviewed in Section V, and the performance of the ITU H.263 codec is analyzed in some depth. Our discussions in Sections VI and VII are focused on the performance of reconfigurable video transceivers. Specifically, in Section VI, no power control is used-which is typically the case in cordless telephones, such as DECT and CT2-while in Section VII, power control is employed, which is characteristic of cellular systems, such as GSM [30], etc. Section VIII proposes a near-instantaneously adaptive or burst-by-burst adaptive code-division multiple-access (CDMA) scheme, which can be invoked in the context of the forthcoming 3G systems, in order to enhance their performance. Lastly, our discussions are concluded in Section IX with a range of system design guidelines. Let us now commence our overview of the range of existing and forthcoming wireless systems and their video transmission capabilities. B. Second-Generation (2G) Wireless SystemsThe existing 2G wireless systems now constitute a mature technology. Although they have not been designed with video communications in mind, with the advent of the specially designed error-resilient, fixed-rate video codecs [27]-[35] proposed by Streit et al., it is nonetheless realistic to provide videophone services over these low-rate schemes. For low-latency interactive videophony these systems have

show abstract

Section: A Advances In Low-rate Video Compressionmentioning

confidence: 99%

Interactive cellular and cordless video telephony: State-of-the-art system design principles and expected performance

2000

View full text Add to dashboard Cite

show abstract

“…Other algorithms for stereo matching include segmented region-based methods (Marapane & Trivedi 1989), phase-based methods (Fleet & Jepson 1990, Fleet et al 1991, topological methods (Fleck 1991), tree matching (Cheng & In 1985), stereo matching using Gabor filters (Sanger 1988, Gennert & Malin 1992, probabilistic methods (Read 2002) and neural networks learned by constraints (Kontanzad et al 1993). A good review of gradient based methods, frequency based methods and hierarchical methods can be found in (Magarey 1997).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Secondly, the distribution of energy between coefficients at different scales is very sensitive to shifts in the input data (Kingsbury & Magarey 1997), i. e. the transforms are not shiftinvariant. However, many wavelets families with complex filter coefficients are now being used (Pan 1996a, Magarey & Kingsbury 1995,1998b, Magarey 1997, Kingsbury & Magarey 1997, Kingsbury 2000a to compensate for the shortcomings of the real wavelet transform. The complex wavelet families have better orientation selectivity (Magarey & Kingsbury 1995, 1998b, Magarey 1997 and are able to exist under the strict conditions for optimality stated by Pan in (Pan 1996 a).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Pan's uniform information matching scheme (Pan 1996b, a) and Magarey and Dick's motion estimation algorithm (Magarey 1997. Kingsbury & Magarey 1997, Magarey & Dick 1998) are tested.…”

Section: Algorithm Choices For Matching Face Imagesmentioning

confidence: 99%

“…In this work two wavelets based methods axe investigated for matching face images: Pan's full information image matching algorithm (Pan 1996b, a) and Magarey's motion estimation algorithm using complex wavelets (Magarey 1997). An overview of both these algorithms is presented in this chapter, with detailed descriptions in Appendices C and D respectively.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automatic Face Recognition Using Stereo Images

Samani

Winkler

Niranjan

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings

View full text Add to dashboard Cite

Face recognition is an important pattern recognition problem, in the study of both natural and artificial learning problems. Compaxed to other biometrics, it is non-intrusive, noninvasive and requires no paxticipation from the subjects. As a result, it has many applications varying from human-computer-interaction to access control and law-enforcement to crowd surveillance.In typical optical image based face recognition systems, the systematic vaxiability arising from representing the three-dimensional (3D) shape of a face by a two-dimensional (21)) illumination intensity matrix is treated as random vaxiability. Multiple examples of the face displaying vaxying pose and expressions axe captured in different imaging conditions. The imaging environment, pose and expressions are strictly controlled and the images undergo rigorous normalisation and pre-processing. This may be implemented in a paxtially or a fully automated system. Although these systems report high classification accuracies (>90%), they lack versatility and tend to fail when deployed outside laboratory conditions.Recently, more sophisticated 3D face recognition systems haxnessing the depth information have emerged. These systems usually employ specialist equipment such as laser scanners and structured light projectors. Although more accurate than 2D optical image based recognition, these systems are equally difficult to implement in a non-co-operative environment.Existing face recognition systems, both 2D and 3D, detract from the main advantages of face recognition and fail to fully exploit its non-intrusive capacity. This is either because they rely too much on subject co-operation, which is not always available, or because they cannot cope with noisy data. The main objective of this work was to investigate the role of depth information in face recognition in a noisy environment. A stereo-based system, inspired by the human binocular vision, was devised using a pair of manually calibrated digital off-the-shelf cameras in a stereo setup to compute depth information. Depth values extracted from 2D intensity images using stereoscopy are extremely noisy, and as a result this approach for face recognition is rare. This was cofirmed by the results of our experimental work. Noise in the set of correspondences, camera calibration and triangulation led to inaccurate depth reconstruction, which in turn led to poor classifier accuracy for both 3D surface matching and 211) depth maps. Psychology literature elucidated that although depth information is crucial to the way humans recognise faces, this information is perceived through disparity information rather than actual depth in the form of familiar structure and texture information seen in 2D images. Hence, dispaxity information can be thought of as neural proxy for depth. Computationally too, depth and disparity are proportional up to camera parameters. Disparity values of sub-pixel accuracy are computed by matching the stereo image pairs to solve the ill-posed Correspondence Problem.A 211) image rep...

show abstract

A generalized model for relative phases based on bilinear representation of natural image series

Wang

Chen

2014

Math Methods in App Sciences

View full text Add to dashboard Cite

a Communicated by T. QianLocal phase is now known to carry information about image features or object motions. But it is harder to use directly compared with amplitude, so far. In this paper, we propose that the relative local phase, which is a function of scale, position and time, really matters in representing the information of image structures or movements. A unified description of relative phase is given in this paper based on a bilinear representation of natural image series via multi-scale orientated dual tree complex wavelets. Then, the behaviors of nontrivial relative phase, especially for their distribution on multi-scale and multi-subband, are investigated. We propose a new generalized model, which is derived from Möbius transform, to describe various relative phases. Numerical experiments for a large amount of test images show that the new model performs best compared with the von Mises or wrapped Cauchy distribution. Especially for those with asymmetric pdf, our function fits with the histogram quite well while the other two may fail. We thus lay a groundwork for relative phase-based image processing methods, such as classification, deblurring and motion perception.

show abstract

Motion estimation using complex wavelets

Cited by 25 publications

References 6 publications

Interactive cellular and cordless video telephony: State-of-the-art system design principles and expected performance

Interactive cellular and cordless video telephony: State-of-the-art system design principles and expected performance

Automatic Face Recognition Using Stereo Images

A generalized model for relative phases based on bilinear representation of natural image series

Contact Info

Product

Resources

About