ÐCurve matching is one instance of the fundamental correspondence problem. Our flexible algorithm is designed to match curves under substantial deformations and arbitrary large scaling and rigid transformations. A syntactic representation is constructed for both curves and an edit transformation which maps one curve to the other is found using dynamic programming. We present extensive experiments where we apply the algorithm to silhouette matching. In these experiments, we examine partial occlusion, viewpoint variation, articulation, and class matching (where silhouettes of similar objects are matched). Based on the qualitative syntactic matching, we define a dissimilarity measure and we compute it for every pair of images in a database of 121 images. We use this experiment to objectively evaluate our algorithm: First, we compare our results to those reported by others. Second, we use the dissimilarity values in order to organize the image database into shape categories. The veridical hierarchical organization stands as evidence to the quality of our matching and similarity estimation.

Abstract-We introduce a new kind of mosaicing, where the position of the sampling strip varies as a function of the input camera location. The new images that are generated this way correspond to a new projection model defined by two slits, termed here the Crossed-Slits (X-Slits) projection. In this projection model, every 3D point is projected by a ray defined as the line that passes through that point and intersects the two slits. The intersection of the projection rays with the imaging surface defines the image. X-Slits mosaicing provides two benefits. First, the generated mosaics are closer to perspective images than traditional pushbroom mosaics. Second, by simple manipulations of the strip sampling function, we can change the location of one of the virtual slits, providing a virtual walkthrough of a X-slits camera; all this can be done without recovering any 3D geometry and without calibration. A number of examples where we translate the virtual camera and change its orientation are given; the examples demonstrate realistic changes in parallax, reflections, and occlusions.

This article evaluates three proposed laws of semantic change. Our claim is that in order to validate a putative law of semantic change, the effect should be observed in the genuine condition but absent or reduced in a suitably matched control condition, in which no change can possibly have taken place. Our analysis shows that the effects reported in recent literature must be substantially revised: (i) the proposed negative correlation between meaning change and word frequency is shown to be largely an artefact of the models of word representation used; (ii) the proposed negative correlation between meaning change and prototypicality is shown to be much weaker than what has been claimed in prior art; and (iii) the proposed positive correlation between meaning change and polysemy is largely an artefact of word frequency. These empirical observations are corroborated by analytical proofs that show that count representations introduce an inherent dependence on word frequency, and thus word frequency cannot be evaluated as an independent factor with these representations.

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Learning in many visual perceptual tasks has been shown to be specific to practiced stimuli, while new stimuli have to be learned from scratch. Here we demonstrate generalization using a novel paradigm in motion discrimination where learning has been previously shown to be specific. We trained subjects to discriminate directions of moving dots, and verified the previous results that learning does not transfer from a trained direction to a new one. However, by tracking the subjects' performance across time in the new direction, we found that their speed of learning doubled. Therefore, we found generalization in a task previously considered too difficult to generalize. We also replicated, in a second experiment, transfer following training with 'easy' stimuli, when the difference between motion directions is enlarged. In a third experiment we found a new mode of generalization: after mastering the task with an easy stimulus, subjects who have practiced briefly to discriminate the easy stimulus in a new direction generalize to a difficult stimulus in that direction. This generalization depends on both the mastering and the brief practice. The specificity of perceptual learning and the dichotomy between learning of 'easy' versus 'difficult' tasks have been assumed to involve different learning processes at different cortical areas. Here we show how to interpret these results in terms of signal detection theory. With the assumption of limited computational capacity, we obtain the observed phenomena--direct transfer and acceleration of learning--for increasing levels of task difficulty. Human perceptual learning and generalization, therefore, concur with a generic discrimination system.