In the QBIC (Query By Image Content) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical ("Give me other images that contain a tumor with a texture like this one"), photo-journalism ("Give me images that have blue at the top and red at the bottom"), and many others in art, fashion, cataloging, retailing, and industry. We describe a set of novel features and similarity measures allowing query by color, texture, and shape of image object. We demonstrate the effectiveness of the QBIC system with normalized precision and recall experiments on test databases containing over 1000 images and 1000 objects populated from commercially available photo clip art images, and of images of airplane silhouettes. We also consider the efficient indexing of these features, specifically addre...

AbstractÐThe Facial Action Coding System (FACS) [23] is an objective method for quantifying facial movement in terms of component actions. This system is widely used in behavioral investigations of emotion, cognitive processes, and social interaction. The coding is presently performed by highly trained human experts. This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. These techniques include analysis of facial motion through estimation of optical flow; holistic spatial analysis, such as principal component analysis, independent component analysis, local feature analysis, and linear discriminant analysis; and methods based on the outputs of local filters, such as Gabor wavelet representations and local principal components. Performance of these systems is compared to naive and expert human subjects. Best performances were obtained using the Gabor wavelet representation and the independent component representation, both of which achieved 96 percent accuracy for classifying 12 facial actions of the upper and lower face. The results provide converging evidence for the importance of using local filters, high spatial frequencies, and statistical independence for classifying facial actions.

Algorithms for approximately optimal quantization of color images are discussed. The distortion measure used is the distance in RGB space. These algorithms are used to compute the color map for low-depth frame buffers in order to allow high-quality static images to be displayed. It is demonstrated that most color images can be very well displayed using only 256 or 512 colors. Thus frame buffers of only 8 or 9 bits can display images that normally require 15 bits or more per pixel. Work reported herein was sponsored by the IBM Corporation though a general grant agreement to MIT dated July 1, 1979. ----------------------------------------------------------------- TABLE OF CONTENTS page I. Introduction ............................................. 4 II. Frame Buffers and Colormaps .............................. 6 III. 1-Dimensional Tapered Quantization .......................17 IV. 3-Dimensional Tapered Quantization .......................27 V. Conclusions and Ideas for Further Study .......

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We have measured how color appearance of squarewave bars varies with stimulus strength and spatial frequency. Observer's adjusted the color of an uniform patch to match the color appearance of the bars in squarewave patterns. We used low to moderate squarewave patterns, from one to eight cycles per degree (cpd). The matches are not photoreceptor matches, but rather are established at more central neural sites. The signals at the putative central sites obey several simple regularities. The cone contrast of the uniform patch is proportional to squarewave stimulus strength (color-homogeneity) and additive with respect to the superposition of equal frequency squarewaves containing different colors (color-superposition). We use the asymmetric matches to derive, from first principles, three patterncolor separable appearance pathways. The matches are explained by two spectrally opponent, spatially lowpass mechanisms and one spectrally positive, spatially bandpass mechanism. The spectr...

Much work has been published on methods for assessing the probable number of clusters or structures within unknown data sets. This paper aims to look in more detail at two methods, a broad parametric method, based around the assumption of Gaussian clusters and the other a non-parametric method which utilises methods of scale-space filtering to extract robust structures within a data set. It is shown that, whilst both methods are capable of determining cluster validity for data sets in which clusters tend towards a multivariate Gaussian distribution, the parametric method inevitably fails for clusters which have a non-Gaussian structure whilst the scale-space method is more robust. Key words : Cluster analysis, maximum likelihood methods, scale-space filtering, probability density estimation. 1 Introduction Most scientific disciplines generate experimental data from an observed system about which we have may have little understanding of the data generating function. The notion that com...

Image-based or light field rendering has received much recent attention as an alternative to traditional geometric methods for modeling and rendering complex objects. A light field represents the radiance flowing through all the points in a scene in all possible directions. We explore two new techniques for efficiently acquiring, storing, and reconstructing light fields in a (nearly) uniform fashion. Both techniques sample the light field by sampling the set of lines that intersect a sphere tightly fit around a given object. Our first approach relies on uniformly subdividing the sphere and representing this subdivision in a compact data structure which allows efficient mapping of image pixels or rays to sphere points and then to subdivision elements. We sample a light field by joining pairs of subdivision elements and store the resulting samples in a multi-resolution, highly compressed fashion that allows efficient rendering. Our second method allows a uniform sampling of all five dime...

The thesis investigates the problem of how information contained in multiple, overlapping images of the same scene may be combined to produce images of superior quality. This area, generically titled frame fusion, offers the possibility of reducing noise, extending the field of view, removal of moving objects, removing blur, increasing spatial resolution and improving dynamic range. As such, this research has many applications in fields as diverse as forensic image restoration, computer generated special effects, video image compression, and digital video editing. An essential enabling step prior to performing frame fusion is image registration, by which an accurate estimate of the point-to-point mapping between views is computed. A robust and efficient algorithm is described to automatically register multiple images using only information contained within the images themselves. The accuracy of this method, and the statistical assumptions upon which it relies, are investigated empirically. Two forms of frame-fusion are investigated. The first is image mosaicing, which is the alignment of multiple images into a single composition representing part of a 3D scene.

This paper describes a hierarchical image registration algorithm for affine motion recovery. The algorithm estimates the affine transformation parameters necessary to register any two digital images misaligned due to rotation, scale, shear, and translation. The parameters are computed iteratively in a coarse-to-fine hierarchical framework using a variation of the Levenberg-Marquadt nonlinear least squares optimization method. This approach yields a robust solution that precisely registers images with subpixel accuracy. A log-polar registration module is introduced to accommodate arbitrary rotation angles and a wide range of scale changes. This serves to furnish a good initial estimate for the optimization-based affine registration stage. We demonstrate the hybrid algorithm on pairs of digital images subjected to large affine motion.

We present a new method of segmentation in which images are segmented by partitions with connected components. For this, first we define two different types of neighborhoods on the space of partitions with connected components of a general graph; neighborhoods of the first type are simple but small, while those of the second type are large but complex; second, we give algorithms which are not computationally costly, for probability simulation and simulated annealing on such spaces using the neighborhoods. In particular Hastings algorithms and generalized Metropolis algorithms are defined to avoid heavy computations in the case of the second type of neighborhoods. To realize segmentation, we propose a hierarchical approach which at each step minimizes a cost function on the space of partitions with connected components of a graph.