Object segmentation is a challenging and important problem in computer vision. The difficulties to obtain accurate segmentations using only the traditional Topdown or Bottom-up approaches have introduced new proposals based on the idea of combining them in order to obtain better results. In this paper we present a novel approach for object segmentation based on the following two steps: 1) overs...

In this paper, we present a novel framework to incorporate bottom-up features and top-down guidance to identify salient objects based on two ideas. The first one automatically encodes object location prior to predict visual saliency without the requirement of center-biased assumption, while the second one estimates image saliency using contrast with respect to background regions. The proposed f...

The fractionation view holds that distinct cognitive operations are mediated by subregions of the inferior parietal lobule (IPL). Within IPL, we hypothesised that retrieval-related activity in different parts of the right supramarginal gyrus (rSMG) may be modulated differentially by information acquired via different combinations of attention signals at encoding. We had two groups of participan...

This paper presents our on-going research at bringing the state-of-the-art in vision and robotics technologies to enhance the emerging minimally invasive surgery, in particular the laparoscopic surgical procedure. A framework that utilizes intelligent visual modeling, recognition, and serving capabilities for assisting the surgeon in maneuvering the scope (camera) in laparoscopy is proposed. Th...

Image segmentation refers to the process to divide an image into non-overlapping meaningful regions according to human perception, which has become a classic topic since the early ages of computer vision. A lot of research has been conducted and has resulted in many applications. However, while many segmentation algorithms exist, yet there are only a few sparse and outdated summarizations avail...

In this paper we propose the Adaptive Scene Dependent Filters (ASDF) to enhance the online learning capabilities of an object recognition system in real-world scenes. The ASDF method proposed extends the idea of unsupervised segmentation to a flexible, highly dynamic image segmentation architecture. We combine unsupervised segmentation to define coherent groups of pixels with a recombination st...

Occurrence of top down and bottom up fatigue cracking in asphaltic pavements is common. Conventional pavement analysis methods ignore the existence of cracks in asphaltic layers. However, it seems that the responses of cracked pavement would not be the same as a pavement without crack. This paper describes effects of crack type, position and length, and vehicles tire inflation pressure and axle...