We introduce a category-independent shape prior for object segmentation. Existing shape priors assume class-specific knowledge, and thus are restricted to cases where the object class is known in advance. The main insight of our approach is that shapes are often shared between objects of different categories. To exploit this “shape sharing” phenomenon, we develop a non-parametric prior that tra...

Segmentation is the art of partitioning an image into different regions where each one has some degree of uniformity in its feature space. A number of methods have been proposed and blind segmentation is one of them. It uses intrinsic image features, such as pixel intensity, color components and texture. However, some virtues, like poor contrast, noise and occlusion, can weaken the procedure. T...

One way to understand something is to break it up into parts. New research indicates that segmenting ongoing activity into meaningful events is a core component of ongoing perception, with consequences for memory and learning. Behavioral and neuroimaging data suggest that event segmentation is automatic and that people spontaneously segment activity into hierarchically organized parts and sub-p...

Word shape information can be helpful in handwriting recognition. It can be used by a segmentation based recognizer to verify the results of the recognition of individual segmented letters. It is often one of the main features used by wholistic recognizers. This paper describes extraction of the word shape information through identification of the middle zone, then ascenders and descenders. Ext...

diagnosis of corneal diseases is possible by measuring and evaluation of corneal thickness in different layers. thus, the need for precise segmentation of corneal layer boundaries is inevitable. obviously, manual segmentation is time‑consuming and imprecise. in this paper, the gaussian mixture model (gmm) is used for automatic segmentation of three clinically important corneal boundaries on opt...

introduction: virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. the segmentation of airways from ct images is a critical step for numerous virtual bronchoscopy applications. materials and methods: to overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy c-mean (fc-fcm), utilized...

Recent work on unsupervised speech segmentation has used self-supervised models with phone and word modules that are trained jointly. This paper instead revisits an older approach to segmentation: bottom-up phone-like unit discovery is performed first, symbolic then top of the discovered units (without influencing lower level). To do this, I propose a new model, chain two segment speech. Both u...

This quasi-experimental study investigated the effect of bottom-up and top-down instructional approaches on English as a foreign language (EFL) vocabulary recall and retention. To this end, 44 high school students from two intact classes were assigned to bottom-up (n = 21) and top-down (n = 23) groups. The participants were exposed to 20 hours of explicit vocabulary instruction during 10 weeks ...

Perceptual tasks such as edge detection, image segmentation, lightness computation and estimation of three-dimensional structure are considered to be low-level or mid-level vision problems and are traditionally approached in a bottom-up, generic and hard-wired way. An alternative to this would be to take a top-down, object-class-specific and example-based approach. In this paper, we present a s...