Using film cutting in interface design

It has been suggested that computer interfaces could be made more usable if their designers utilized cinematography techniques, which have evolved to guide the viewer through a narrative despite frequent discontinuities in the presented scene (i.e., cuts between shots). Because of differences between the domains of film and interface design, it is not straightforward to understand how such techniques can be transferred. May and Barnard (1995) argued that a psychological model of watching film could support such a transference. This article presents an extended account of this model, which allows identification of the practice of collocation of objects of interest in the same screen position before and after a cut. To verify that filmmakers do, in fact, use such techniques successfully, eye movements were measured while participants watched the entirety of a commerciall

On the merits of the Gaussian Mixture as a model for oriented edgel distributions

The aim of this report is to establish the credibility of the Gaussian Mixture Model (GMM) as a model for the distributions of oriented edgels of rigid and biological objects in noisy images. This is tackled in two stages: first, the response of the Soble filter to noisy pixels is analysed to show that the result holds for smooth ridid objects. Second, arguments are presented to support the proposition that the model can also effectively capture the added uncertainty introduced by natural shape variation, as found in images of biological objects. The result has particular application in the extension of the Generalized Hough Transform (GHT) to deformable shapes; in particular if offers a tailored and manipulable alternative to the non-parametric kernel density estimate used by Ecabert and Thiran

Human face profile recognition

The purpose of this thesis is to implement an automatic person identification system based on face profiles. Each person\u27s face profile can be quite unique within a small sample population and therefore it can be used as the basis of an automatic person identification system. To quantify human face profiles for use in the recognition system, Fourier descriptors are used to describe the open curve extracted from a face profile. Fourier descriptors in the low-frequency range are shown to be useful for human face profile recognition. By using 16 Fourier coefficients, a correct recognition rate of 92% for 60 subjects was achieved

Similarity Measurement of Breast Cancer Mammographic Images Using Combination of Mesh Distance Fourier Transform and Global Features

Similarity measurement in breast cancer is an important aspect of determining the vulnerability of detected masses based on the previous cases. It is used to retrieve the most similar image for a given mammographic query image from a collection of previously archived images. By analyzing these results, doctors and radiologists can more accurately diagnose early-stage breast cancer and determine the best treatment. The direct result is better prognoses for breast cancer patients. Similarity measurement in images has always been a challenging task in the field of pattern recognition. A widely-adopted strategy in Content-Based Image Retrieval (CBIR) is comparison of local shape-based features of images. Contours summarize the orientations and sizes images, allowing for heuristic approach in measuring similarity between images. Similarly, global features of an image have the ability to generalize the entire object with a single vector which is also an important aspect of CBIR. The main objective of this paper is to enhance the similarity measurement between query images and database images so that the best match is chosen from the database for a particular query image, thus decreasing the chance of false positives. In this paper, a method has been proposed which compares both local and global features of images to determine their similarity. Three image filters are applied to make this comparison. First, we filter using the mesh distance Fourier descriptor (MDFD), which is based on the calculation of local features of the mammographic image. After this filter is applied, we retrieve the five most similar images from the database. Two additional filters are applied to the resulting image set to determine the best match. Experiments show that this proposed method overcomes shortcomings of existing methods, increasing accuracy of matches from 68% to 88%

Proceedings of the 4th field robot event 2006, Stuttgart/Hohenheim, Germany, 23-24th June 2006

Zeer uitgebreid verslag van het 4e Fieldrobotevent, dat gehouden werd op 23 en 24 juni 2006 in Stuttgart/Hohenhei