Traditional and new principles of perceptual grouping

Perceptual grouping refers to the process of determining which regions and parts of the visual scene belong together as parts of higher order perceptual units such as objects or patterns. In the early 20th century, Gestalt psychologists identified a set of classic grouping principles which specified how some image features lead to grouping between elements given that all other factors were held constant. Modern vision scientists have expanded this list to cover a wide range of image features but have also expanded the importance of learning and other non-image factors. Unlike early Gestalt accounts which were based largely on visual demonstrations, modern theories are often explicitly quantitative and involve detailed models of how various image features modulate grouping. Work has also been done to understand the rules by which different grouping principles integrate to form a final percept. This chapter gives an overview of the classic principles, modern developments in understanding them, and new principles and the evidence for them. There is also discussion of some of the larger theoretical issues about grouping such as at what stage of visual processing it occurs and what types of neural mechanisms may implement grouping principles

Identifying the information for the visual perception of relative phase

The production and perception of coordinated rhythmic movement are very specifically structured. For production and perception, 0° mean relative phase is stable, 180° is less stable, and no other state is stable without training. It has been hypothesized that perceptual stability characteristics underpin the movement stability characteristics, which has led to the development of a phase-driven oscillator model (e.g., Bingham, 2004a, 2004b). In the present study, a novel perturbation method was used to explore the identity of the perceptual information being used in rhythmic movement tasks. In the three conditions, relative position, relative speed, and frequency (variables motivated by the model) were selectively perturbed. Ten participants performed a judgment task to identify 0° or 180° under these perturbation conditions, and 8 participants who had been trained to visually discriminate 90° performed the task with perturbed 90° displays. Discrimination of 0° and 180° was unperturbed in 7 out of the 10 participants, but discrimination of 90° was completely disrupted by the position perturbation and was made noisy by the frequency perturbation. We concluded that (1) the information used by most observers to perceive relative phase at 0° and 180° was relative direction and (2) becoming an expert perceiver of 90° entails learning a new variable composed of position and speed

Symmetry sensitivities of Derivative-of-Gaussian filters

We consider the measurement of image structure using linear filters, in particular derivative-of-Gaussian (DtG) filters, which are an important model of V1 simple cells and widely used in computer vision, and whether such measurements can determine local image symmetry. We show that even a single linear filter can be sensitive to a symmetry, in the sense that specific responses of the filter can rule it out. We state and prove a necessary and sufficient, readily computable, criterion for filter symmetry-sensitivity. We use it to show that the six filters in a second order DtG family have patterns of joint sensitivity which are distinct for 12 different classes of symmetry. This rich symmetry-sensitivity adds to the properties that make DtG filters well-suited for probing local image structure, and provides a set of landmark responses suitable to be the foundation of a nonarbitrary system of feature categories

The Impact of Shape on the Perception of Euler Diagrams

Euler diagrams are often used for visualizing data collected into sets. However, there is a significant lack of guidance regarding graphical choices for Euler diagram layout. To address this deficiency, this paper asks the question `does the shape of a closed curve affect a user's comprehension of an Euler diagram?' By empirical study, we establish that curve shape does indeed impact on understandability. Our analysis of performance data indicates that circles perform best, followed by squares, with ellipses and rectangles jointly performing worst. We conclude that, where possible, circles should be used to draw effective Euler diagrams. Further, the ability to discriminate curves from zones and the symmetry of the curve shapes is argued to be important. We utilize perceptual theory to explain these results. As a consequence of this research, improved diagram layout decisions can be made for Euler diagrams whether they are manually or automatically drawn

Visual and Contextual Modeling for the Detection of Repeated Mild Traumatic Brain Injury.

Currently, there is a lack of computational methods for the evaluation of mild traumatic brain injury (mTBI) from magnetic resonance imaging (MRI). Further, the development of automated analyses has been hindered by the subtle nature of mTBI abnormalities, which appear as low contrast MR regions. This paper proposes an approach that is able to detect mTBI lesions by combining both the high-level context and low-level visual information. The contextual model estimates the progression of the disease using subject information, such as the time since injury and the knowledge about the location of mTBI. The visual model utilizes texture features in MRI along with a probabilistic support vector machine to maximize the discrimination in unimodal MR images. These two models are fused to obtain a final estimate of the locations of the mTBI lesion. The models are tested using a novel rodent model of repeated mTBI dataset. The experimental results demonstrate that the fusion of both contextual and visual textural features outperforms other state-of-the-art approaches. Clinically, our approach has the potential to benefit both clinicians by speeding diagnosis and patients by improving clinical care

Perception of Lower Extremity Loads in Stroke Survivors

Objective: This study aimed to improve our understanding of static and dynamic lower extremity sensory perception and the impact of sensory impairments on the control of walking in stroke survivors. Methods: Using a custom, real-time unloading system, we tested load perception at heel strike, mid stance and push off in 10 stroke survivors and compared their performance to 10 age-matched and 5 young adult control subjects. Dynamic load perception was based on a judgment of which leg was bearing more load, which was altered on a step by step basis. We also examined lower extremity static load perception, coordination, proprioception, balance, and gait symmetry. Results: The stroke survivors performed significantly worse than the control subjects in dynamic load perception, coordination, proprioception, balance and gait symmetry. Gait symmetry correlated with static and dynamic load perception measures but not with age, proprioception, coordination, and balance. Conclusions: Sensory deficits related to load detection in the impaired limb could result in an increased uncertainty of limb load and a gait strategy in which stroke survivors minimize loading of the impaired limb. Significance: This new method of measuring lower extremity dynamic load perception provides a framework for understanding gait-related sensory impairments in stroke survivors