Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

GrabCutSFM : how 3D information improves unsupervised object segmentation

In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called Grab- CutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.

Nonparametric semantic segmentation for 3D street scenes

In this paper we propose a method to generate a large scale and accurate dense 3D semantic map of street scenes. A dense 3D semantic model of the environment can significantly improve a number of robotic applications such as autonomous driving, navigation or localisation. Instead of using offline trained classifiers for semantic segmentation, our approach employs a data-driven, nonparametric method to parse scenes which easily scale to a large environment and generalise to different scenes. We use stereo image pairs collected from cameras mounted on a moving car to produce dense depth maps which are combined into a global 3D reconstruction using camera poses from stereo visual odometry. Simultaneously, 2D automatic semantic segmentation using a nonparametric scene parsing method is fused into the 3D model. Furthermore, the resultant 3D semantic model is improved with the consideration of moving objects in the scene. We demonstrate our method on the publicly available KITTI dataset and evaluate the performance against manually generated ground truth.

Aircraft collision avoidance using spherical visual predictive control and single point features

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions

We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

Very sensitive fiber Bragg grating accelerometer using transverse forces with an easy over-range protection and low cross axial sensitivity

The first fiber Bragg grating (FBG) accelerometer using direct transverse forces is demonstrated by fixing the FBG by its two ends and placing a transversely moving inertial object at its middle. It is very sensitive because a lightly stretched FBG is more sensitive to transverse forces than axial forces. Its resonant frequency and static sensitivity are analyzed by the classic spring-mass theory, assuming the axial force changes little. The experiments show that the theory can be modified for cases where the assumption does not hold. The resonant frequency can be modified by a linear relationship experimentally achieved, and the static sensitivity by an alternative method proposed. The principles of the over-range protection and low cross axial sensitivity are achieved by limiting the movement of the FBG and were validated experimentally. The sensitivities 1.333 and 0.634 nm/g were experimentally achieved by 5.29 and 2.83 gram inertial objects at 10 Hz from 0.1 to 0.4 g (g = 9.8 m/s 2), respectively, and their resonant frequencies were around 25 Hz. Their theoretical static sensitivities and resonant frequencies found by the modifications are 1.188 nm/g and 26.81 Hz for the 5.29 gram one and 0.784 nm/g and 29.04 Hz for the 2.83 gram one, respectively.

Information organisation behaviours within everyday life : an exploration using the diary method

This paper presents the results from a study of information behaviours (IB), with specific focus on information- organisation-related behaviours conducted as part of a larger daily diary study with 40 participants. The findings indicate that organisation of information in everyday life is problematic due to various factors, specifically temporal and spatial ones, i.e., the passage of time, along with the difference in the physical environment between when the information was organised and when the information is retrieved. These have implications for information organisation schemas, and point toward the need for a context-sensitive model of information organisation that reflects the relation between information objects, information representation, and information users.

I’m friends with Louie the Fly, not Mortein : Conceptualising the new brand relationships on social media

Spokes-characters are ‘...animated beings or objects, created to promote a product, service or idea’ (Phillips 1996, p.155). They were first used in the late 1800s when they emerged as registered trademarks, but the use of spokes-characters for marketing communications has since grown, owing to their ability to remind consumers about a product, transfer positive associations to a brand, and give a corporate company a more ‘personal’ face (Callcott and Lee 1995). One example is the Michelin Man, who has served as spokes-character for Michelin tyres since 1898, after starting out in print advertising. Spokes-characters have become important brand representatives, no longer seen as simply entertaining cartoons featured in television and magazine advertisements. Corporations have now extended their use to interactive, social media platforms, where a consumer can be ‘friends’ with a spokes-character via Facebook, read their comments on the latest iPhone release through Twitter, and watch their family histories being documented on YouTube (see Figure 1). The interactions that consumers once had with two-dimensional spokes-characters have undergone significant transformation in the digital space. With spokes-character Facebook pages achieving significant numbers of ‘likes’ and interactions with consumers, one question concerns whether this strategy is creating characters that are more engaging than the brands they represent, and what impact this has on brand outcomes.

Preparing for performance capture #1

This video article articulates two exercises that have been developed to respond to the need for preparedness in the growing field of Performance Capture. The first is called Walking Through (Delbridge 2013), where the actor navigates a series of objects that exist in screen space through a developed sense of the existing physical particularities of the studio and an interaction with a screen (or feedback loop). The second exercise is called The Donut (Delbridge 2013), where the performer continues to navigate screen space but this time does so through the literal stepping through of a Torus in the virtual – again with nothing but the studio infrastructure and the screen as a guide. Notions of Motion Captured performance infer the existence of an interface that combines performer with system, separating (or intervening in) the space between performance and the screen. It is precisely the effect and provided opportunity of the intermediary device on the practice, craft and preparedness of the actor as they navigate the connection between 3D screen space and the physical properties of the studio that is examined here. Defining the scope of current practice for the contemporary actor is a key construct of this challenge, with the most appropriate definition revolving around the provision of a required mixture of performance and content for live, mediated, framed and variously captured formats. One of these particular formats is Performance Capture. The exercises presented here are two from a series, developed over a three year study that contribute to our understanding of the potential for a training regimen to be developed for the rigors of Performance Capture.

Understanding the actualization of affordances: A study in the process modeling context

The affordances concept describes the possibilities for goal-oriented action that technical objects offer to specified users. This notion has received growing attention from IS researchers. However, few studies have gone beyond contextualizing parts of the concept to a specific setting – the tip of the iceberg. In this research-in-progress paper, we report on our efforts to further develop the IS discipline’s understanding of affordances from informational objects. Specifically, we seek to extend extant theory on the origin and actualization of affordances. We develop a model that describes the process by which affordances are perceived and actualized and their dependence on information and actualization effort. We illustrate our emergent theory in the context of conceptual process models used by analysts for purposes of information systems analysis and design. We offer suggestions for operationalizing and testing this model empirically, and provide details about our design of a mixed-methods study currently in progress.

An introduction to the application of (case 1) best–worst scaling in marketing research

We review and discuss recent developments in best–worst scaling (BWS) that allow researchers to measure items or objects on measurement scales with known properties. We note that BWS has some distinct advantages compared with other measurement approaches, such as category rating scales or paired comparisons. We demonstrate how to use BWS to measure subjective quantities in two different empirical examples. One of these measures preferences for weekend getaways and requires comparing relatively few objects; a second measures academics' perceptions of the quality of academic marketing journals and requires comparing a significantly large set of objects. We conclude by discussing some limitations and future research opportunities related to BWS.

The paradox of autistic art

Certain autistic children whose linguistic ability is virtually nonexistent can draw natural scenes from memory with astonishing accuracy. In particular their drawings display convincing perspective. In contrast, normal children of the same preschool age group and even untrained adults draw primitive schematics or symbols of objects which they can verbally identify. These are usually conceptual outlines devoid of detail. It is argued that the difference between autistic child artists and normal individuals is that autistic artists make no assumptions about what is to be seen in their environment. They have not formed mental representations of what is significant and consequently perceive all details as equally important. Equivalently, they do not impose visual or linguistic schema -- a process necessary for rapid conceptualisation in a dynamic existence, especially when the information presented to the eye is incomplete.

Autistic artists give clues to cognition

Certain autistic children whose linguistic ability is virtually nonexistent can draw natural scenes from memory with astonishing accuracy. In particular their drawings display convincing perspective. In contrast, normal children of the same preschool age group and even untrained adults draw primitive schematics or symbols of objects which they can verbally identify. These are usually conceptual outlines devoid of detail. It is argued that the difference between autistic child artists and normal individuals is that autistic artists make no assumptions about what is to be seen in their environment. They have not formed mental representations of what is significant and consequently perceive all details as equally important. Equivalently, they do not impose visual or linguistic schema -- a process necessary for rapid conceptualisation in a dynamic existence, especially when the information presented to the eye is incomplete.

Dislocations of desire : the transnational movement of gifts within the Vietnamese diaspora

Gifts have intrigued and challenged scholars ever since interest in the subject was piqued by Marcel Mauss who, in 1925, wrote the book The gift: The form and reason for exchange in archaic societies. Although ethnographic studies of giftgiving have been mostly confined to small-scale communities, scholars have more recently turned their attention to industrial societies, with studies of Christmas giving, Japanese gift-giving, etc. Now, as studies of consumption are entering a phase of efflorescence, it is time to re-evaluate gift-giving. The recent rapid expansion in the transnational flow of people, objects and ideas has had an impact on the social conditions associated with new global patterns of consumption. In this atmosphere of overlapping cultural, economic and political worlds, there is a need to look again at the objects that pass between us as gifts...

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.