Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Fast and robust stereo object recognition for spheres

The paper presents a fast and robust stereo object recognition method. The method is currently unable to identify the rotation of objects. This makes it very good at locating spheres which are rotationally independent. Approximate methods for located non-spherical objects have been developed. Fundamental to the method is that the correspondence problem is solved using information about the dimensions of the object being located. This is in contrast to previous stereo object recognition systems where the scene is first reconstructed by point matching techniques. The method is suitable for real-time application on low-power devices.

The effectiveness of marketing communication within the immersive environment

Immersive environments are part of a recent media innovation that allow users to become so involved within a computer-based simulated environment that they feel part of that virtual world (Grigorovici, 2003). A specific example is Second Life, which is an internet-based, three-dimensional immersive virtual world in which users create an online representation of themselves (an avatar) to play games and interact socially with thousands of people simultaneously. This study focuses on Second Life as an example of an immersive environment, as it is the largest adult freeform virtual world, home to 12 million avatars (IOWA State University, 2008). Already in Second Life there are more than 100 real-life brands from a range of industries, including automotive, professional services, and consumer goods and travel, among others (KZero, 2007; New Business Horizons, 2009). Compared to traditional advertising media, this interactive media can immerse users in the environment. As a result of this interactivity, users can become more involved with a virtual environment, resulting in prolonged usage over weeks, months and even years. Also, it can facilitate presence. Despite these developments, little is known about the effectiveness of marketing messages in a virtual world context. Marketers are incorporating products into Second Life using a strategy of online product placement. This study, therefore, explores the perceived effectiveness of online product placement in Second Life in terms of effects on product/brand recall, purchase intentions and trial. This research examines the association between individuals’ involvement with Second Life and online product placement effectiveness, as well as the relationship between individuals’ Second Life involvement and the effectiveness of online product placement. In addition, it investigates the association of immersion and product placement involvement. It also examines the impact of product placement involvement on online product placement effectiveness and the role of presence in affecting this relationship. An exploratory study was conducted for this research using semi-structured in-depth interviews face-to-face, email-based and in-world. The sample comprised 24 active Second Life users. Results indicate that product placement effectiveness is not directly associated with Second Life involvement, but rather effectiveness is impacted through the effect of Second Life involvement on product placement involvement. A positive relationship was found between individuals’ product placement involvement and online product placement effectiveness. Findings also indicate that online product placement effectiveness is not directly associated with immersion. Rather, it appears that effectiveness is impacted through the effect of immersion on product placement involvement. Moreover, higher levels of presence appear to have a positive impact on the relationship between product placement involvement and product placement effectiveness. Finally, a model was developed from this qualitative study for future testing. In terms of theoretical contributions, this study provides a new model for testing the effectiveness of product placement within immersive environments. From a methodological perspective, in-world interviews as a new research method were undertaken. In terms of a practical contribution, findings identified useful information for marketers and advertising agencies that aim to promote their products in immersive virtual environments like Second Life.

High dynamic range stereo vision for outdoor mobile robotics

We present a technique for high-dynamic range stereo for outdoor mobile robot applications. Stereo pairs are captured at a number of different exposures (exposure bracketing), and combined by projecting the 3D points into a common coordinate frame, and building a 3D occupancy map. We present experimental results for static scenes with constant and dynamic lighting as well as outdoor operation with variable and high contrast lighting conditions.

Combined optic-flow and stereo-based navigation of urban canyons for a UAV

We present a novel vision-based technique for navigating an Unmanned Aerial Vehicle (UAV) through urban canyons. Our technique relies on both optic flow and stereo vision information. We show that the combination of stereo and optic-flow (stereo-flow) is more effective at navigating urban canyons than either technique alone. Optic flow from a pair of sideways-looking cameras is used to stay centered in a canyon and initiate turns at junctions, while stereo vision from a forward-facing stereo head is used to avoid obstacles to the front. The technique was tested in full on an autonomous tractor at CSIRO and in part on the USC autonomous helicopter. Experimental results are presented from these two robotic platforms operating in outdoor environments. We show that the autonomous tractor can navigate urban canyons using stereoflow, and that the autonomous helicopter can turn away from obstacles to the side using optic flow. In addition, preliminary results show that a single pair of forward-facing fisheye cameras can be used for both stereo and optic flow. The center portions of the fisheye images are used for stereo, while flow is measured in the periphery of the images.

Reliability analysis of transform-based stereo matching techniques, and a new matching constraint

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Practical applications for stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics and industrial automation. The initial motivation behind this work was to produce a stereo vision sensor for mining automation applications. For such applications, the input stereo images would consist of close range scenes of rocks. A fundamental problem faced by matching algorithms is the matching or correspondence problem. This problem involves locating corresponding points or features in two images. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This work implemented a number of areabased matching algorithms to assess their suitability for this application. Area-based techniques were investigated because of their potential to yield dense depth maps, their amenability to fast hardware implementation, and their suitability to textured scenes such as rocks. In addition, two non-parametric transforms, the rank and census, were also compared. Both the rank and the census transforms were found to result in improved reliability of matching in the presence of radiometric distortion - significant since radiometric distortion is a problem which commonly arises in practice. In addition, they have low computational complexity, making them amenable to fast hardware implementation. Therefore, it was decided that matching algorithms using these transforms would be the subject of the remainder of the thesis. An analytic expression for the process of matching using the rank transform was derived from first principles. This work resulted in a number of important contributions. Firstly, the derivation process resulted in one constraint which must be satisfied for a correct match. This was termed the rank constraint. The theoretical derivation of this constraint is in contrast to the existing matching constraints which have little theoretical basis. Experimental work with actual and contrived stereo pairs has shown that the new constraint is capable of resolving ambiguous matches, thereby improving match reliability. Secondly, a novel matching algorithm incorporating the rank constraint has been proposed. This algorithm was tested using a number of stereo pairs. In all cases, the modified algorithm consistently resulted in an increased proportion of correct matches. Finally, the rank constraint was used to devise a new method for identifying regions of an image where the rank transform, and hence matching, are more susceptible to noise. The rank constraint was also incorporated into a new hybrid matching algorithm, where it was combined a number of other ideas. These included the use of an image pyramid for match prediction, and a method of edge localisation to improve match accuracy in the vicinity of edges. Experimental results obtained from the new algorithm showed that the algorithm is able to remove a large proportion of invalid matches, and improve match accuracy.

Methacrylate-functionalized oligomers based on lactide, E-caprolactone and trimethylene carbonate for application in stereo-lithography

Photo-curable biodegradable macromers were prepared by ring opening polymerization of D,L-lactide (DLLA), (similar to)-caprolactone (CL) and 1,3-trimethylene carbonate (TMC) in the presence of glycerol or sorbitol as initiator and stannous octoate as catalyst, and subsequent methacrylation of the terminal hydroxyl groups. These methacrylated macromers, ranging in molecular weight from approximately 700 to 6000 g/mol, were cross-linked using ultraviolet (UV) light to form biodegradable networks. Homogeneous networks with high gel contents were prepared. One of the resins based on PTMC was used to prepare three-dimensional structures by stereo-lithography using a commercially available apparatus.

Methacrylate-functionalized oligomers based on lactide, ε- caprolactone and trimethylene carbonate for application in stereo-lithography

Photo-curable biodegradable macromers were prepared by ring opening polymerization of D,L-lactide (DLLA), ε-caprolactone (CL) and 1,3-trimethylene carbonate (TMC) in the presence of glycerol or sorbitol as initiator and stannous octoate as catalyst, and subsequent methacrylation of the terminal hydroxyl groups. These methacrylated macromers, ranging in molecular weight from approximately 700 to 6000 g/mol, were cross-linked using ultraviolet (UV) light to form biodegradable networks. Homogeneous networks with high gel contents were prepared. One of the resins based on PTMC was used to prepare three-dimensional structures by stereo-lithography using a commercially available apparatus.

Finding the remote: Immersive learning in an outback community

Real-world design education projects present particular challenges when in a place remote from and distinctively different to students’ familiar territory. The teaching challenge is to assist students to translate the skills they learn at university into an entirely new context, facilitating a project they will learn from, and the community will value. In 2008 QUT design and engineering students undertook a project called Linking Karumba for this remote Queensland town. They engaged with a landscape, climate and community dramatically different from their base in urban Brisbane, and in a fortnight produced locally responsive strategic planning options. The theoretical approach to this was twofold: they needed to make a rapid shift along a continuum from being “outsiders” towards becoming “insiders” (Relph 1976), and to create designs responsive to local distinctiveness (Cumberlidge and Musgrave 2007). This paper outlines Linking Karumba’s teaching strategy via an analogy with the “immersion” method in bilingual education. Three teaching methods were adopted. Firstly, the overall framework drew on Brockbank and McGill (1998), and Thomas’ (2006a) approaches to student reflective practice. Within this, Girot’s “Four Trace Concepts” (1999) inspired exercises for finding Karumba and moving toward insideness; and a program of community engagement sought immersion in local distinctiveness, and “conversation” between the differing forms of knowledge and capacities embedded within the community and students (Armstrong 1999, Thomas 2006). The responsiveness of the student work to the character of Karumba’s culture and environment indicated remarkable levels of immersion, and the community highly valued the project outcomes: four strategic planning options which attracted $830 000 in state government funding for implementation.

Unaided stereo vision based pose estimation

This paper presents the development of a low-cost sensor platform for use in ground-based visual pose estimation and scene mapping tasks. We seek to develop a technical solution using low-cost vision hardware that allows us to accurately estimate robot position for SLAM tasks. We present results from the application of a vision based pose estimation technique to simultaneously determine camera poses and scene structure. The results are generated from a dataset gathered traversing a local road at the St Lucia Campus of the University of Queensland. We show the accuracy of the pose estimation over a 1.6km trajectory in relation to GPS ground truth.

A Taxonomy of image matching techniques for stereo vision

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.