This paper proposes to infer accurately a 3D shape of an object captured by a depth camera from multiple view points. The Generalised Relaxed Radon Transform (GR2T) [1] is used here to merge all depth images in a robust kernel density estimate that models the surface of an object in the 3D space. The kernel is tailored to capture the uncertainty associated with each pixel in the depth images. T...

We present an alignment framework for object detection using a hierarchy of 3D polygonal models. One difficulty with alignment methods is that the high-dimensional transformation space makes finding potential candidate states a time-consuming task. This is an important consideration in our approach, as an exhaustive search is applied on a densely-sampled state space in order to avoid local mini...

A framework for computer-aided analysis of mammograms is described. General computer vision algorithms are combined with application specific procedures in a hierarchical fashion. The system is under development and is currently limited to detection of a few types of suspicious areas. The image features are extracted by using feature extraction methods where wavelet techniques are utilized. A l...

In this research, two techniques of pixel-based and object-based image analysis were investigated and compared for providing land use map in arid basin of Mokhtaran, Birjand. Using Landsat satellite imagery in 2015, the classification of land use was performed with three object-based algorithms of supervised fuzzy-maximum likelihood, maximum likelihood, and K-nearest neighbor. Nine combinations...

BACKGROUND AND PURPOSE Identifying tissue at risk for infarction is an important goal of stroke imaging. This study was performed to determine whether pixel-based apparent diffusion coefficient (ADC) and signal intensity ratio are helpful diffusion-weighted (DW) imaging metrics to predict tissue at risk for infarction. METHODS Twelve patients presenting with acute hemispheric strokes underwen...

This paper presents a programmable, energy-efficient and realtime object detection accelerator using deformable parts models (DPM), with 2x higher accuracy than traditional rigid body models. With 8 deformable parts detection, three methods are used to address the high computational complexity: classification pruning for 33x fewer parts classification, vector quantization for 15x memory size re...

In this project we present detection the motion in video frames using background frame Matching. These document video surveillance systems have become widely available to ensure safety and security in both the public and private sectors due to incidents of terrorist activity and other social problems. This paper proposes a novel motion detection method with a background model module and an obje...

Our group has previously used machine learning techniques to develop computational systems to automatically analyse fluorescence microscope images and classify the location of the depicted protein. Based on this work, we developed a system, the Subcellular Location Image Finder (slif), which mines images from scientific journals for analysis. For some of the images in journals, the system is ab...

A strong earthquake of magnitude 6.8 struck the Mediterranean coast of Algeria on 21 May 2003 and the city of Zemmouri in Boumerdes province was most heavily damaged. QuickBird satellite observed the Zemmouri area on 23 May 2003. By image sharpening, buildings, cars and even debris can clearly be identified in a natural colour image. Preliminarily, the present authors performed visual damage in...