Robust visual tracking based on online learning sparse representation

Handling appearance variations is a very challenging problem for visual tracking. Existing methods usually solve this problem by relying on an effective appearance model with two features: (1) being capable of discriminating the tracked target from its background, (2) being robust to the target's appearance variations during tracking. Instead of integrating the two requirements into the appearance model, in this paper, we propose a tracking method that deals with these problems separately based on sparse representation in a particle filter framework. Each target candidate defined by a particle is linearly represented by the target and background templates with an additive representation error. Discriminating the target from its background is achieved by activating the target templates or the background templates in the linear system in a competitive manner. The target's appearance variations are directly modeled as the representation error. An online algorithm is used to learn the basis functions that sparsely span the representation error. The linear system is solved via ℓ1 minimization. The candidate with the smallest reconstruction error using the target templates is selected as the tracking result. We test the proposed approach using four sequences with heavy occlusions, large pose variations, drastic illumination changes and low foreground-background contrast. The proposed approach shows excellent performance in comparison with two latest state-of-the-art trackers.

Visual enhancement of touch in spatial body representation

Perception of our own bodies is based on integration of visual and tactile inputs, notably by neurons in the brain’s parietal lobes. Here we report a behavioural consequence of this integration process. Simply viewing the arm can speed up reactions to an invisible tactile stimulus on the arm. We observed this visual enhancement effect only when a tactile task required spatial computation within a topographic map of the body surface and the judgements made were close to the limits of performance. This effect of viewing the body surface was absent or reversed in tasks that either did not require a spatial computation or in which judgements were well above performance limits. We consider possible mechanisms by which vision may influence tactile processing.

Multiple feature points representation in target localization of wireless visual sensor networks

This paper discusses the target localization problem in wireless visual sensor networks. Additive noises and measurement errors will affect the accuracy of target localization when the visual nodes are equipped with low-resolution cameras. In the goal of improving the accuracy of target localization without prior knowledge of the target, each node extracts multiple feature points from images to represent the target at the sensor node level. A statistical method is presented to match the most correlated feature point pair for merging the position information of different sensor nodes at the base station. Besides, in the case that more than one target exists in the field of interest, a scheme for locating multiple targets is provided. Simulation results show that, our proposed method has desirable performance in improving the accuracy of locating single target or multiple targets. Results also show that the proposed method has a better trade-off between camera node usage and localization accuracy.

The representation of the ipsilateral visual field in human cerebral cortex

Previous studies of cortical retinotopy focused on influences from the contralateral visual field, because ascending inputs to cortex are known to be crossed. Here, functional magnetic resonance imaging was used to demonstrate and analyze an ipsilateral representation in human visual cortex. Moving stimuli, in a range of ipsilateral visual field locations, revealed activity: (i) along the vertical meridian in retinotopic (presumably lower-tier) areas; and (ii) in two large branches anterior to that, in presumptive higher-tier areas. One branch shares the anterior vertical meridian representation in human V3A, extending superiorly toward parietal cortex. The second branch runs antero-posteriorly along lateral visual cortex, overlying motion-selective area MT. Ipsilateral stimuli sparing the region around the vertical meridian representation also produced signal reductions (perhaps reflecting neural inhibition) in areas showing contralaterally driven retinotopy. Systematic sampling across a range of ipsilateral visual field extents revealed significant increases in ipsilateral activation in V3A and V4v, compared with immediately posterior areas V3 and VP. Finally, comparisons between ipsilateral stimuli of different types but equal retinotopic extent showed clear stimulus specificity, consistent with earlier suggestions of a functional segregation of motion vs. form processing in parietal vs. temporal cortex, respectively.

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

Issues of collaboration, representation, meaning and emotions:utilising participant-led visual diaries to capture the everyday lives of people in mid to later life

In recent years there has been an increasing use of visual methods in ageing research. There are, however, limited reflections and critical explorations of the implications of using visual methods in research with people in mid to later life. This paper examines key methodological complexities when researching the daily lives of people as they grow older and the possibilities and limitations of using participant-generated visual diaries. The paper will draw on our experiences of an empirical study, which included a sample of 62 women and men aged 50 years and over with different daily routines. Participant-led photography was drawn upon as a means to create visual diaries, followed by in-depth, photo-elicitation interviews. The paper will critically reflect on the use of visual methods for researching the daily lives of people in mid to later life, as well as suggesting some wider tensions within visual methods that warrant attention. First, we explore the extent to which photography facilitates a ‘collaborative’ research process; second, complexities around capturing the ‘everydayness’ of daily routines are explored; third, the representation and presentation of ‘self’ by participants within their images and interview narratives is examined; and, finally, we highlight particular emotional considerations in visualising daily life.

Representation of Maximally Regular Textures in Human Visual Cortex

Copyright © 2016 the authors 0270-6474/16/360714-16$15.00/0. This research was supported by National Science Foundation INSPIRE Grant 1248076, which was awarded to Y.L. and A.M.N.

RICH AND EFFICIENT VISUAL DATA REPRESENTATION

Increasing the size of training data in many computer vision tasks has shown to be very effective. Using large scale image datasets (e.g. ImageNet) with simple learning techniques (e.g. linear classifiers) one can achieve state-of-the-art performance in object recognition compared to sophisticated learning techniques on smaller image sets. Semantic search on visual data has become very popular. There are billions of images on the internet and the number is increasing every day. Dealing with large scale image sets is intense per se. They take a significant amount of memory that makes it impossible to process the images with complex algorithms on single CPU machines. Finding an efficient image representation can be a key to attack this problem. A representation being efficient is not enough for image understanding. It should be comprehensive and rich in carrying semantic information. In this proposal we develop an approach to computing binary codes that provide a rich and efficient image representation. We demonstrate several tasks in which binary features can be very effective. We show how binary features can speed up large scale image classification. We present learning techniques to learn the binary features from supervised image set (With different types of semantic supervision; class labels, textual descriptions). We propose several problems that are very important in finding and using efficient image representation.

Criteria for graphic representation in musical scores: Visual elements in musical scores

A interdisciplinaridade entre a música e as artes visuais tem sido explorado por conceituados teóricos e filósofos, embora não exista muito na área da interpretação visual do grafismo de partituras musicais. Este estudo investiga como os grafismos na notação e símbolos musicais afectam o intérprete na sua transformação em som, com referência especial a partituras contemporâneas, que utilizam notação menos convencional para a criação de uma interpretação por sugestão. Outras relações entre o som e o visual são exploradas, incluindo a sinestesia, a temporalidade e a relação entre obra de arte e público. O objectivo desta dissertação é a de constituir um estudo inovativo sobre partituras musicais contemporâneas, simultaneamente do ponto de vista musical e visual. Finalmente, também vai mais longe, incluindo desenhos da própria autora inspirados e motivados pela música. Estes já não cumprem uma função de notação convencional para o músico, embora existe uma constante possibilidade de uma reinterpretação. ABSTRACT; The inter-disciplinarity between music and visual art has been explored by leading theorists and philosophers, though very little exists in the area of the visual interpretation of graphic musical scores. This study looks at how the graphics of musical notation and symbols affect the performer in transforming them into sound, with particular reference to contemporary scores that use non¬conventional notation to create an interpretation through suggestion. Other sound-visual relationships are explored, including synaesthesia, temporality and the interconnection between work of art and audience or public. This dissertation aims to be an innovative study of contemporary musical scores, from a musical as well as visual perspective. Finally, it takes a step further with drawings of my own, directly inspired and motivated by the music. These no longer fulfil a conventionally notational function for the musician, yet the potential for a re-interpretation is ever-present.

Experiential knowledge representation and the design of product usability

The topic of designers’ knowledge and how they conduct design process has been widely investigated in design research. Understanding theoretical and experiential knowledge in design has involved recognition of the importance of designers’ experience of experiencing, seeing, and absorbing ideas from the world as points of reference (or precedents) that are consulted whenever a design problem arises (Lawson, 2004). Hence, various types of design knowledge have been categorized (Lawson, 2004), and the nature of design knowledge continues to be studied (Cross, 2006); nevertheless, the study of the experiential aspects embedded in design knowledge is a topic not fully addressed. In particular there has been little emphasis on the investigation of the ways in which designers’ individual experience influences different types of design tasks. This research focuses on the investigation of the ways in which designers inform a usability design process. It aims to understand how designers design product usability, what informs their process, and the role their individual experience (and episodic knowledge) plays within the design process. This paper introduces initial outcomes from an empirical study involving observation of a design task that emphasized usability issues. It discusses the experiential knowledge observed in the visual representations (sketches) produced by designers as part of the design tasks. Through the use of visuals as means to represent experiential knowledge, this paper presents initial research outcomes to demonstrate how designers’ individual experience is integrated into design tasks and communicated within the design process. Initial outcomes demonstrate the influence of designers’ experience in the design of product usability. It is expected that outcomes will help identify the causal relationships between experience, context of use, and product usability, which will contribute to enhance our understanding about the design of user-product interactions.