Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representation and recognition in vision
Representation and recognition in vision
Measuring and predicting visual fidelity
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
ACM Transactions on Graphics (TOG)
Evaluation of Two Principal Approaches to Objective Image Quality Assessment
IV '04 Proceedings of the Information Visualisation, Eighth International Conference
Haptic Rendering: Introductory Concepts
IEEE Computer Graphics and Applications
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Object feature validation using visual and haptic similarity ratings
ACM Transactions on Applied Perception (TAP)
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Which object properties matter most in human perception may well vary according to sensory modality, an important consideration for the design of multimodal interfaces. In this study, we present a similarity-based method for comparing the perceptual importance of object properties across modalities and show how it can also be used to perceptually validate computational measures of object properties. Similarity measures for a set of three-dimensional (3D) objects varying in shape and texture were gathered from humans in two modalities (vision and touch) and derived from a set of standard 2D and 3D computational measures (image and mesh subtraction, object perimeter, curvature, Gabor jet filter responses, and the Visual Difference Predictor (VDP)). Multidimensional scaling (MDS) was then performed on the similarity data to recover configurations of the stimuli in 2D perceptual/computational spaces. These two dimensions corresponded to the two dimensions of variation in the stimulus set: shape and texture. In the human visual space, shape strongly dominated texture. In the human haptic space, shape and texture were weighted roughly equally. Weights varied considerably across subjects in the haptic experiment, indicating that different strategies were used. Maps derived from shape-dominated computational measures provided good fits to the human visual map. No single computational measure provided a satisfactory fit to the map derived from mean human haptic data, though good fits were found for individual subjects; a combination of measures with individually-adjusted weights may be required to model the human haptic similarity judgments. Our method provides a high-level approach to perceptual validation, which can be applied in both unimodal and multimodal interface design.