The purpose of the present experiment is to further understand the effect of levels of processing (top-down vs. bottom-up) on the perception of movement kinematics and primitives for grasping actions in order to gain insight into possible primitives used by the mirror system. In the present study, we investigated the potential of identifying such primitives using an action segmentation task. Sp...

his paper presents a novel range image segmentation algorithm based on a newly proposed obust estimator: Adaptive Scale Sample Consensus (ASSC) [28]. The proposed algorithm is a odel-based top-down technique and directly extracts the required primitives (models) from the aw images. Compared with current popular methods (region-based and edge-based methods), the lgorithm is very robust to noisy ...

Most speaker diarization systems fit into one of two categories: bottom-up or top-down. Bottom-up systems are the most popular but can sometimes suffer from instability from merging and stopping criteria difficulties. Top-down systems deliver competitive results but are particularly prone to poor model initialization which often leads to large variations in performance. This paper presents a ne...

Image segmentation and object recognition are among the most fundamental problems in computer vision, and the potential interaction between these tasks has been discussed for many years. The usefulness of recognition for segmentation has been demonstrated with various top-down segmentation algorithms, however, the impact of bottom-up image segmentation as pre-processing for object recognition i...

The joint tasks of object recognition and object segmentation from a single image are complex in their requirement of not only correct classification, but also deciding exactly which pixels belong to the object. Exploring all possible pixel subsets is prohibitively expensive, leading to recent approaches which use unsupervised image segmentation to reduce the size of the configuration space. Im...

Tattoo segmentation is challenging due to the complexity and large variance in tattoo structures. We have developed a segmentation algorithm for finding tattoos in an image. Our basic idea is split-merge: split each tattoo image into clusters through a bottom-up process, learn to merge the clusters containing skin and then distinguish tattoo from the other skin via top-down prior in the image i...

The field of object detection has seen dramatic performance improvements in the last few years. Most of these gains are attributed to bottom-up, feedforward ConvNet frameworks. However, in case of humans, top-down information, context and feedback play an important role in doing object detection. This paper investigates how we can incorporate top-down information and feedback in the state-of-th...

A major objection to top-down accounts of lexical recognition has been that they are incompatible with an account of acquisition, it being argued that bottom-up segmentation must precede lexical acquisition. We counter this objection by presenting a top-down account of lexical acquisition. This is made possible by the adoption of a flexible criterion as to what may constitute a lexical item dur...