Giuseppe Boccignone

Foveated shot detection for video segmentation

We view scenes in the real world by moving our eyes three to four times each second and integrating information across subsequent fixations (foveation points). By taking advantage of this fact, in this paper we propose an original approach to partitioning of a video into shots based on a foveated representation of the video. More precisely, the shot-change detection method is related to the computation, at each time instant, of a consistency measure of the fixation sequences generated by an ideal observer looking at the video. The proposed scheme aims at detecting both abrupt and gradual transitions between shots using a single technique, rather than a set of dedicated methods. Results on videos of various content types are reported and validate the proposed approach.

Computer aided detection of microcalcifications in digital mammograms

Microcalcification detection is widely used for early diagnosis of breast cancer. Nevertheless, mammogram visual analysis is a complex task for expert radiologists. In this paper, we present a new method for computer aided detection of microcalcifications in digital mammograms. The detection is performed on the wavelet transformed image. The calcifications are separated from the background by exploiting the evaluation of Renyis information at the different decomposition levels of the wavelet transform. Experiments are performed on a standard and publicly available dataset and the results are evaluated with respect to recent achievements reported in the literature.

Bayesian Integration of Face and Low-Level Cues for Foveated Video Coding

We present a Bayesian model that allows to automatically generate flxations/foveations and that can be suitably exploited for compression purposes. The twofold aim of this work is to investigate how the exploitation of high-level perceptual cues provided by human faces occurring in the video can enhance the compression process without reducing the perceived quality of the video and to validate such assumption with an extensive and principled experimental protocol. To such end, the model integrates top-down and bottom-up cues to choose the fixation point on a video frame: at the highest level, a fixation is driven by prior information and by relevant objects, namely human faces, within the scene; at the same time, local saliency together with novel and abrupt visual events contribute by triggering lower level control. The performance of the resulting video compression system has been evaluated with respect to both the perceived quality of foveated video clips and the compression gain with an extensive evaluation campaign, which has eventually involved 200 subjects.

Small target detection using wavelets

Presents a method for the detection of small objects embedded in a noisy background. The detection is performed on the wavelet transformed image. After a preliminary de-noising pass, the objects are separated from background by exploiting the evaluation of Renyis information at the different decomposition levels of the wavelet transform. We apply the proposed technique to detect microcalcifications in digital mammographic images.

Visuomotor Characterization of Eye Movements in a Drawing Task

Understanding visuomotor coordination requires the study of tasks that engage mechanisms for the integration of visual and motor information; in this paper we choose a paradigmatic yet little studied example of such a task, namely realistic drawing. On the one hand, our data indicate that the motor task has little influence on which regions of the image are overall most likely to be fixated: salient features are fixated most often. Viceversa, the effect of motor constraints is revealed in the temporal aspect of the scanpaths: (1) subjects direct their gaze to an object mostly when they are acting upon (drawing) it; and (2) in support of graphically continuous hand movements, scanpaths resemble edge-following patterns along image contours. For a better understanding of such properties, a computational model is proposed in the form of a novel kind of Dynamic Bayesian Network, and simulation results are compared with human eye-hand data.

Context-sensitive queries for image retrieval in digital libraries

In this paper we show how to achieve a more effective Query By Example processing, by using active mechanisms of biological vision, such as saccadic eye movements and fixations. In particular, we discuss the way to generate two fixation sequences from a query image Iq and a test image It of the data set, respectively, and how to compare the two sequences in order to compute a similarity measure between the two images. Meanwhile, we show how the approach can be used to discover and represent the hidden semantic associations among images, in terms of categories, which in turn drive the query process.

Multiscale contrast enhancement of medical images

We present results obtained by different contrast enhancement methods applied to medical images. We take into account classical histogram specification, local and wavelet-based techniques and a novel approach for multiscale contrast enhancement. The latter, whose rationale grounds in theories of visual perception, exploits a local definition of the Fechner-Webers contrast within the context of a non-linear scale-space representation generated by anisotropic diffusion. Our experimental fields concerns a difficult kind of medical images, namely digital mammographic images.

A multiscale contrast enhancement method

This paper contributes a novel approach to contrast enhancement. The proposed approach measures local contrast within the context of a nonlinear scale-space representation. The original image is locally probed at multiple resolutions generated through anisotropic diffusion. Once local contrast has been estimated across an optimal range of scales, its value is used to enhance the initial image. Due to the choice of the anisotropic scale-space, the method also accounts for nonlinear edge contributions. Properties of local contrast within scale-space are introduced and discussed.

Ecological Sampling of Gaze Shifts

Visual attention guides our gaze to relevant parts of the viewed scene, yet the moment-to-moment relocation of gaze can be different among observers even though the same locations are taken into account. Surprisingly, the variability of eye movements has been so far overlooked by the great majority of computational models of visual attention. In this paper we present the ecological sampling model, a stochastic model of eye guidance explaining such variability. The gaze shift mechanism is conceived as an active random sampling that the foraging eye carries out upon the visual landscape, under the constraints set by the observable features and the global complexity of the landscape. By drawing on results reported in the foraging literature, the actual gaze relocation is eventually driven by a stochastic differential equation whose noise source is sampled from a mixture of α-stable distributions. This way, the sampling strategy proposed here allows to mimic a fundamental property of the eye guidance mechanism: where we choose to look next at any given moment in time, it is not completely deterministic, but neither is it completely random To show that the model yields gaze shift motor behaviors that exhibit statistics similar to those displayed by human observers, we compare simulation outputs with those obtained from eye-tracked subjects while viewing complex dynamic scenes.

Entropy-based representation of image information

Loss of information in images undergoing fine-to-coarse transformations is analysed by using an approach based on the theory of irreversible processes. In the case of grey level images, entropy variation along scales is used to characterize basic, low-level information and to identify perceptual components of the image, such as shape and texture. Here an extension of the approach to colour images is proposed. Spatio-chromatic information is defined, which depends on cross-interactions between the different colour channels. Examples illustrating the use of spatio-chromatic information are presented, related to pattern recognition and active vision. 2002 Elsevier Science B.V. All rights reserved.