A simple, intuitive camera calibration tool for natural images

The paper reports an interactive tool for calibrating a camera, suitable for use in outdoor scenes. The motivation for the tool was the need to obtain an approximate calibration for images taken with no explicit calibration data. Such images are frequently presented to research laboratories, especially in surveillance applications, with a request to demonstrate algorithms. The method decomposes the calibration parameters into intuitively simple components, and relies on the operator interactively adjusting the parameter settings to achieve a visually acceptable agreement between a rectilinear calibration model and his own perception of the scene. Using the tool, we have been able to calibrate images of unknown scenes, taken with unknown cameras, in a matter of minutes. The standard of calibration has proved to be sufficient for model-based pose recovery and tracking of vehicles.

The sediment trapping efficiency of the macro-tidal Daly Estuary, tropical Australia

Field studies were carried out on the water and sediment dynamics in the tropical, macro-tidal, Daly Estuary. The estuary is shallow, very-turbid, about 100 km long, and the entrance is funnel-shape. In the wet, high flow season, normal tidal ranges can be suppressed in the estuary, depending on inflow rates, and freshwater becomes dominant up to the mouth. At that time a fraction of the fine sediment load is exported offshore as a bottom-tagging nepheloid layer after the sediment falls out of suspension of the thin, near-surface, river plume. The remaining fraction and the riverine coarse sediment form a large sediment bar 10 km long, up to 6 m in height and extending across the whole width of the channel near the mouth. This bar, as well as shoals in the estuary, partially pond the mid- to upper-estuary. This bar builds up from the deposition of riverine sediment during a wet season with high runoff and can raise mean water level by up to 2 m in the upper estuary in the low flow season. This ponding effect takes about three successive dry years to disappear by the sediment forming the bar being redistributed all over the estuary by tidal pumping of fine and coarse sediment in the dry season, which is the low flow season. The swift reversal of the tidal currents from ebb to flood results in macro-turbulence that lasts about 20 min. Bed load transport is preferentially landward and occurs only for water currents greater than 0.6 m s(-1). This high value of the threshold velocity suggests that the sand may be cemented by the mud. The Daly Estuary thus is a leaky sediment trap with an efficiency varying both seasonally and inter-annually. (c) 2006 Elsevier Ltd. All rights reserved.

The trapping and decomposition of toxic gases such as hydrogen cyanide using modified mesoporous silicates

Selected silicas were modified with the covalently bound ligand 2,6-bis(benzoxazoyl)pyridine (BBOP), equilibrated with copper(II) nitrate, then challenged with toxic vapour containing HCN (8000 mg m(-3) at 80% relative humidity). The modified SBA-15 material (Cu-BBOP-SBA-15) had an improved breakthrough time for HCN (36 min at a flow rate of 30 cm(3) min(-1)) when compared to the other siliceous materials prepared in this study, equating to a hydrogen cyanide capacity of 58 mg g(-1), which is close to a reference activated carbon adsorbent (24 min at 50 cm(3) min(-1)) that can trap 64 mg g(-1). The enhanced performance observed with Cu-BBOP-SBA-15 has been related to the greater accessibility of the functional groups, arising from the ordered nature of the interconnected porous network and large mesopores of 5.5 nm within the material modified with the Cu(II)-BBOP complex. Modified MCM-41 and MCM-48 materials (Cu-BBOP-MCM-41 and Cu-BBOP-MCM-48) were found to have lower hydrogen cyanide capacities (38 and 32 mg g(-1) respectively) than the Cu-BBOP-SBA-15 material owing to the restricted size of the pores (2.2 and <2 nm respectively). The materials with poor nano-structured ordering were found to have low hydrogen cyanide capacities, between 11 and 19 mg g(-1), most likely owing to limited accessibility of the functional groups. (C) 2004 Elsevier Inc. All rights reserved.

Robust background model for pixel based people counting using a single uncalibrated camera

Several pixel-based people counting methods have been developed over the years. Among these the product of scale-weighted pixel sums and a linear correlation coefficient is a popular people counting approach. However most approaches have paid little attention to resolving the true background and instead take all foreground pixels into account. With large crowds moving at varying speeds and with the presence of other moving objects such as vehicles this approach is prone to problems. In this paper we present a method which concentrates on determining the true-foreground, i.e. human-image pixels only. To do this we have proposed, implemented and comparatively evaluated a human detection layer to make people counting more robust in the presence of noise and lack of empty background sequences. We show the effect of combining human detection with a pixel-map based algorithm to i) count only human-classified pixels and ii) prevent foreground pixels belonging to humans from being absorbed into the background model. We evaluate the performance of this approach on the PETS 2009 dataset using various configurations of the proposed methods. Our evaluation demonstrates that the basic benchmark method we implemented can achieve an accuracy of up to 87% on sequence ¿S1.L1 13-57 View 001¿ and our proposed approach can achieve up to 82% on sequence ¿S1.L3 14-33 View 001¿ where the crowd stops and the benchmark accuracy falls to 64%.

A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.

Trapping of palindromic ligands within native transthyretin prevents amyloid formation

Transthyretin (TTR) amyloidosis is a fatal disease for which new therapeutic approaches are urgently needed. We have designed two palindromic ligands, 2,2’-(4,4’-(heptane 1,7-diylbis(oxy))bis(3,5-dichloro-4,1-phenylene)) bis(azanediyl)dibenzoic acid (mds84) and 2,2’-(4,4’-(undecane-1,11-diylbis(oxy))bis(3,5-dichloro-4,1-phenylene)) bis(azanediyl)dibenzoic acid (4ajm15), that are rapidly bound by native wild-type TTR in whole serum and even more avidly by amyloidogenic TTR variants. One to one stoichiometry, demonstrable in solution and by MS, was confirmed by X-ray crystallographic analysis showing simultaneous occupation of both T4 binding sites in each tetrameric TTR molecule by the pair of ligand head groups. Ligand binding by native TTR was irreversible under physiological conditions, and it stabilized the tetrameric assembly and inhibited amyloidogenic aggregation more potently than other known ligands. These superstabilizers are orally bioavailable and exhibit low inhibitory activity against cyclooxygenase (COX). They offer a promising platform for development of drugs to treat and prevent TTR amyloidosis.

Surveillance camera calibration from observations of a pedestrian

Calibrated cameras are an extremely useful resource for computer vision scenarios. Typically, cameras are calibrated through calibration targets, measurements of the observed scene, or self-calibrated through features matched between cameras with overlapping fields of view. This paper considers an approach to camera calibration based on observations of a pedestrian and compares the resulting calibration to a commonly used approach requiring that measurements be made of the scene.

Modeling camera orientation and 3D structure from a sequence of images taken by a perambulating commercial video camera

In this paper we report the degree of reliability of image sequences taken by off-the-shelf TV cameras for modeling camera rotation and reconstructing 3D structure using computer vision techniques. This is done in spite of the fact that computer vision systems usually use imaging devices that are specifically designed for the human vision. Our scenario consists of a static scene and a mobile camera moving through the scene. The scene is any long axial building dominated by features along the three principal orientations and with at least one wall containing prominent repetitive planar features such as doors, windows bricks etc. The camera is an ordinary commercial camcorder moving along the axial axis of the scene and is allowed to rotate freely within the range +/- 10 degrees in all directions. This makes it possible that the camera be held by a walking unprofessional cameraman with normal gait, or to be mounted on a mobile robot. The system has been tested successfully on sequence of images of a variety of structured, but fairly cluttered scenes taken by different walking cameramen. The potential application areas of the system include medicine, robotics and photogrammetry.