Recognizing 3-D Objects Using 2-D Images

We discuss a strategy for visual recognition by forming groups of salient image features, and then using these groups to index into a data base to find all of the matching groups of model features. We discuss the most space efficient possible method of representing 3-D models for indexing from 2-D data, and show how to account for sensing error when indexing. We also present a convex grouping method that is robust and efficient, both theoretically and in practice. Finally, we combine these modules into a complete recognition system, and test its performance on many real images.

Imaging of three-dimensional objects in emission electron microscopy

Under investigation by emission electron microscopy, the shape and size of three-dimensional objects are distorted because of the appearance of a characteristic potential relief and a possible contact potential difference between the particles and the substrate. An estimation of these effects for spherical particles is made. It is shown that the apparent size of particles observed in an emission electron microscope (EEM) could be increased as well as decreased depending on the relation between the work functions of the particle and the substrate. The corresponding formulae are given and several possibilities are shown which permit us to determine from the EEM image the real size of particles and their work function relative to the substrate.

Layered Graphical Models for Tracking Partially-Occluded Objects

Partial occlusions are commonplace in a variety of real world computer vision applications: surveillance, intelligent environments, assistive robotics, autonomous navigation, etc. While occlusion handling methods have been proposed, most methods tend to break down when confronted with numerous occluders in a scene. In this paper, a layered image-plane representation for tracking people through substantial occlusions is proposed. An image-plane representation of motion around an object is associated with a pre-computed graphical model, which can be instantiated efficiently during online tracking. A global state and observation space is obtained by linking transitions between layers. A Reversible Jump Markov Chain Monte Carlo approach is used to infer the number of people and track them online. The method outperforms two state-of-the-art methods for tracking over extended occlusions, given videos of a parking lot with numerous vehicles and a laboratory with many desks and workstations.

Vector Associative Maps: Unsupervised Real-time Error-based Learning and Control of Movement Trajectories

This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models clarify how a child, or untrained robot, can learn to reach for objects that it sees. Piaget has provided basic insights with his concept of a circular reaction: As an infant makes internally generated movements of its hand, the eyes automatically follow this motion. A transformation is learned between the visual representation of hand position and the motor representation of hand position. Learning of this transformation eventually enables the child to accurately reach for visually detected targets. Grossberg and Kuperstein have shown how the eye movement system can use visual error signals to correct movement parameters via cerebellar learning. Here it is shown how endogenously generated arm movements lead to adaptive tuning of arm control parameters. These movements also activate the target position representations that are used to learn the visuo-motor transformation that controls visually guided reaching. The AVITE model presented here is an adaptive neural circuit based on the Vector Integration to Endpoint (VITE) model for arm and speech trajectory generation of Bullock and Grossberg. In the VITE model, a Target Position Command (TPC) represents the location of the desired target. The Present Position Command (PPC) encodes the present hand-arm configuration. The Difference Vector (DV) population continuously.computes the difference between the PPC and the TPC. A speed-controlling GO signal multiplies DV output. The PPC integrates the (DV)·(GO) product and generates an outflow command to the arm. Integration at the PPC continues at a rate dependent on GO signal size until the DV reaches zero, at which time the PPC equals the TPC. The AVITE model explains how self-consistent TPC and PPC coordinates are autonomously generated and learned. Learning of AVITE parameters is regulated by activation of a self-regulating Endogenous Random Generator (ERG) of training vectors. Each vector is integrated at the PPC, giving rise to a movement command. The generation of each vector induces a complementary postural phase during which ERG output stops and learning occurs. Then a new vector is generated and the cycle is repeated. This cyclic, biphasic behavior is controlled by a specialized gated dipole circuit. ERG output autonomously stops in such a way that, across trials, a broad sample of workspace target positions is generated. When the ERG shuts off, a modulator gate opens, copying the PPC into the TPC. Learning of a transformation from TPC to PPC occurs using the DV as an error signal that is zeroed due to learning. This learning scheme is called a Vector Associative Map, or VAM. The VAM model is a general-purpose device for autonomous real-time error-based learning and performance of associative maps. The DV stage serves the dual function of reading out new TPCs during performance and reading in new adaptive weights during learning, without a disruption of real-time operation. YAMs thus provide an on-line unsupervised alternative to the off-line properties of supervised error-correction learning algorithms. YAMs and VAM cascades for learning motor-to-motor and spatial-to-motor maps are described. YAM models and Adaptive Resonance Theory (ART) models exhibit complementary matching, learning, and performance properties that together provide a foundation for designing a total sensory-cognitive and cognitive-motor autonomous system.

Real-life Social Attention in Children with Autism Spectrum Disorders

Autism is a neuro-developmental disorder defined by atypical social behaviour, of which atypical social attention behaviours are among the earliest clinical markers (Volkmar et al., 1997). Eye tracking studies using still images and movie clips have provided a method for the precise quantification of atypical social attention in ASD. This is generally characterised by diminished viewing of the most socially pertinent regions (eyes), and increased viewing of less socially informative regions (body, background, objects) (Klin et al., 2002; Riby & Hancock, 2008, 2009). Ecological validity within eye tracking studies has become an increasingly important issue. As of yet, however, little is known about the precise nature of the atypicalities of social attention in ASD in real-life. Objectives: To capture and quantify gaze patterns for children with an ASD within a real life setting, compared to two Typically Developing (TD) comparison groups. Methods: Nine children with an ASD were compared to two age matched TD groups – a verbal (N=9) and a non-verbal (N=9) comparison group. A real-life scenario was created involving an experimenter posing as a magician, and consisted of 3 segments: a conversation segment; a magic trick segment; and a puppet segment. The first segment explored children’s attentional preferences during a real-life conversation; the magic trick segment explored children’s use of the eyes as a communicative cue, and the puppet segment explored attention capture. Finally, part of the puppet section explored children’s use of facial information in response to an unexpected event. Results: The most striking difference between the groups was the diminished viewing of the eyes by the ASD group in comparison to both control groups. This was found particularly during the conversation segment, but also during the magic trick segment, and during the puppet segment. When in conversation, participants with ASD were found to spend a greater proportion time looking off-screen, in comparison to TD participants. There was also a tendency for the ASD group to spend a greater proportion of time looking to the mouth of the experimenter. During the magic trick segment, despite the fact that the eyes were not predictive of a correct location, both TD comparison groups continued to use the eyes as a communicative cue, whereas the ASD group did not. In the puppet segment, all three groups spent a similar amount of time looking between the puppet and regions of the experimenter’s face. However, in response to an unexpected event, the ASD group were significantly slower to fixate back on the experimenter’s face. Conclusions: The results demonstrate the reduced salience of socially pertinent information for children with ASD in real life, and they provide support for the findings from previous eye tracking studies involving scene viewing. However, the results also highlight a pattern looking off-screen for both the TD and ASD groups. This eye movement behaviour is likely to be associated specifically with real-life interaction, as it has functional relevance (Doherty-Sneddon et al., 2002). However, the fact that it is significantly increased in the ASD group has implications for their understanding of real life social interactions.

Architecture for real-time coordination of multiple autonomous mobile units

Interest on using teams of mobile robots has been growing, due to their potential to cooperate for diverse purposes, such as rescue, de-mining, surveillance or even games such as robotic soccer. These applications require a real-time middleware and wireless communication protocol that can support an efficient and timely fusion of the perception data from different robots as well as the development of coordinated behaviours. Coordinating several autonomous robots towards achieving a common goal is currently a topic of high interest, which can be found in many application domains. Despite these different application domains, the technical problem of building an infrastructure to support the integration of the distributed perception and subsequent coordinated action is similar. This problem becomes tougher with stronger system dynamics, e.g., when the robots move faster or interact with fast objects, leading to tighter real-time constraints. This thesis work addressed computing architectures and wireless communication protocols to support efficient information sharing and coordination strategies taking into account the real-time nature of robot activities. The thesis makes two main claims. Firstly, we claim that despite the use of a wireless communication protocol that includes arbitration mechanisms, the self-organization of the team communications in a dynamic round that also accounts for variable team membership, effectively reduces collisions within the team, independently of its current composition, significantly improving the quality of the communications. We will validate this claim in terms of packet losses and communication latency. We show how such self-organization of the communications can be achieved in an efficient way with the Reconfigurable and Adaptive TDMA protocol. Secondly, we claim that the development of distributed perception, cooperation and coordinated action for teams of mobile robots can be simplified by using a shared memory middleware that replicates in each cooperating robot all necessary remote data, the Real-Time Database (RTDB) middleware. These remote data copies, which are updated in the background by the selforganizing communications protocol, are extended with age information automatically computed by the middleware and are locally accessible through fast primitives. We validate our claim showing a parsimonious use of the communication medium, improved timing information with respect to the shared data and the simplicity of use and effectiveness of the proposed middleware shown in several use cases, reinforced with a reasonable impact in the Middle Size League of RoboCup.

Benefits & drawbacks of different means of interaction for placing objects above a video footage

Public Display Systems (PDS) increasingly have a greater presence in our cities. These systems provide information and advertising specifically tailored to audiences in spaces such as airports, train stations, and shopping centers. A large number of public displays are also being deployed for entertainment reasons. Sometimes designing and prototyping PDS come to be a laborious, complex and a costly task. This dissertation focuses on the design and evaluation of PDS at early development phases with the aim of facilitating low-effort, rapid design and the evaluation of interactive PDS. This study focuses on the IPED Toolkit. This tool proposes the design, prototype, and evaluation of public display systems, replicating real-world scenes in the lab. This research aims at identifying benefits and drawbacks on the use of different means to place overlays/virtual displays above a panoramic video footage, recorded at real-world locations. The means of interaction studied in this work are on the one hand the keyboard and mouse, and on the other hand the tablet with two different techniques of use. To carry out this study, an android application has been developed whose function is to allow users to interact with the IPED Toolkit using the tablet. Additionally, the toolkit has been modified and adapted to tablets by using different web technologies. Finally the users study makes a comparison about the different means of interaction.

Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·

Biologically motivated model for object detection and identification in real-world scenes

The classical computer vision methods can only weakly emulate some of the multi-level parallelisms in signal processing and information sharing that takes place in different parts of the primates’ visual system thus enabling it to accomplish many diverse functions of visual perception. One of the main functions of the primates’ vision is to detect and recognise objects in natural scenes despite all the linear and non-linear variations of the objects and their environment. The superior performance of the primates’ visual system compared to what machine vision systems have been able to achieve to date, motivates scientists and researchers to further explore this area in pursuit of more efficient vision systems inspired by natural models. In this paper building blocks for a hierarchical efficient object recognition model are proposed. Incorporating the attention-based processing would lead to a system that will process the visual data in a non-linear way focusing only on the regions of interest and hence reducing the time to achieve real-time performance. Further, it is suggested to modify the visual cortex model for recognizing objects by adding non-linearities in the ventral path consistent with earlier discoveries as reported by researchers in the neuro-physiology of vision.

Robust real-time tracking for visual surveillance

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright (C) 2007 Hindawi Publishing Corporation. All rights reserved.

Using objects to coordinate design activity in interaction

The coordination of design is a multi-faceted problem in construction. In design interactions in particular the real-time coordination of design activity is a persistent concern. The use of objects to coordinate the activity of design is studied as this happens in interactions between an architect and a building user group, in a setting where maintaining awareness of the design situation is important. An account of ways in which this was accomplished and how design activity is coordinated through interactional practices is provided. The empirical analyses examine design interaction from an ethnomethodological/conversation analysis (EM/CA) informed perspective to examine: ways in which mutual orientation to design issues are accomplished, how objects can provide a resource for the recognition of the activities of others and ways in which objects might be observable as momentarily intelligible. Subtle interactional practices involving talk, gesture and gaze were some of the small ways in which mutual orientation to the design actions of others became observable. The production of actions sequentially, in response to another's action, marked the real-time coordination of design moves in this setting. The relevance of accounts of micro-interaction to develop understanding of design activity and how it is coordinated are considered.

Colour relationalism and the real deliverances of introspection

Colour relationalism holds that the colours are constituted by relations to subjects. Anti-relationalists have claimed that this view stands in stark contrast to our phenomenally-informed, pre-theoretic intuitions. Is this claim right? Cohen and Nichols’ recent empirical study suggests not, as about half of their participants seemed to be relationalists about colour. Despite Cohen and Nichols’ study, we think that the anti-relationalist’s claim is correct. We explain why there are good reasons to suspect that Cohen and Nichols’ experimental design skewed their results in favour of relationalism. We then run an improved study and find that most of our participants seem to be anti-relationalists. We find some other interesting things too. Our results suggest that the majority of ordinary people find it no less intuitive that colours are objective than that shapes are objective. We also find some evidence that when those with little philosophical training are asked about the colours of objects, their intuitions about colour and shape cases are similar, but when asked about people’s colour ascriptions, their intuitions about colour and shape cases differ.

Wave optics analysis by phase-shifting real-time holographic interferometry

The purpose of this work is to study the potentialities in the phase-shifting real-time holographic interferometry using photorefractive crystals as the recording medium for wave-optics analysis in optical elements and non-linear optical materials. This technique was used for obtaining quantitative measurements from the phase distributions of the wave front of lens and lens systems along the propagation direction with in situ visualization, monitoring and analysis in real time. (C) 2008 Elsevier GmbH. All rights reserved.

Light-induced lens analysis in photorefractive crystals employing phase-shifting real-time holographic interferometry

The purpose of this work is to study the potentialities of phase-shifting real-time holographic interferometry for the analysis of light-induced lens in photoreffactive and nonlinear optical materials. We show that this technique can be used for quantitative evaluation of the phase distribution of a wavefront changed by a light-induced lens and, consequently, the refractive index changes in these materials. The basic principle of this technique combines real-time holographic interferometry with phase-shifting technique for interferogram analysis. This method is demonstrated with in situ visualization, monitoring and analysis in real-time and uses a Bi(12)SiO(20) crystal as the holographic medium and a Bi(12)TiO(20) as the test sample. (C) 2008 Elsevier B.V. All rights reserved.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.