Properties Of Human Perception Research Articles

A set of visual feature descriptors and their combination in a low-level description scheme

This paper reports about descriptors for basic visual information features, which have been developed in the context of the forthcoming MPEG-7 standard. The four basic features supported are color, texture, shape and motion. A search engine system has been developed which supports combinations of basic feature descriptors in a low-level description scheme for similarity-based retrieval of visual (image and video) data. All basic descriptors have been developed so that invariance against common transformations of visual material, e.g. filtering, contrast/color manipulation, resizing, etc., is achieved, and that they are fitted to human perception properties. Furthermore, descriptors have been designed to allow fast, coarse-to-fine search procedures. Elements described in this contribution have been proposed for the MPEG-7 standard. They are currently either included in the MPEG-7 Experimentation Model (XM) or investigated within core experiments, which are performed during the standard's development.

Spatial and contextual factors in human performance on the travelling salesperson problem.

The travelling salesperson problem (TSP) provides a realistic and practical example of a visuo-spatial problem-solving task. In previous research, we have found that the quality of solutions produced by human participants for small TSPs compares well with solutions from a range of computer algorithms. We have proposed that the ability of participants to find solutions reflects the natural properties of human perception, solutions being found through global perceptual processing of the problem array to extract a best figure from the TSP points. In this paper, we extend the study of human performance on the task in order to understand further how human abilities are utilised in solving real-world TSPs. The results of experiment 1 show that high levels of solution quality are maintained in solving larger TSPs than had been investigated previously with human participants, and that the presence of an implied real-world context in the problems has no effect upon performance. Experiment 2 demonstrated that the presence of regularity in the point layout of a TSP can facilitate performance. This was confirmed in experiment 3, where effects of the internality of point clusters were also found. All three experiments were consistent with a global, perceptually based approach to the problem by participants. We suggest that the role of perceptual processing in spatial problem-solving is an important area for further research in both theoretical and applied domains.

Towards increasing speech recognition error rates

In the field of Automatic Speech Recognition (ASR) research, it is conventional to pursue those approaches that reduce the word error rate. However, it is the authors' belief that this seemingly sensible strategy often leads to the suppression of innovation. The leading approaches to ASR have been tuned for years, effectively optimizing on test data for a local minimum in the space of available techniques. In this case, almost any sufficiently new approach will necessarily hurt the accuracy of existing systems and thus increase the error rate. However, if progress is to be made against the remaining difficult problems, new approaches will most likely be necessary. In this paper, we discuss some research directions for ASR that may not always yield an immediate and guaranteed decrease in error rate but which hold some promise for ultimately improving performance in the end applications. Issues that will be addressed in this paper include: discrimination between rival utterance models, the role of prior information in speech recognition, merging the language and acoustic models, feature extraction and temporal information, and decoding procedures reflecting human perceptual properties.

Objective picture quality scale by neural network fed the distortion factors to the input layers

AbstractIt is important to improve the picture quality of an image reconstructed by computer simulation. It is also important that the performance of coders be evaluated. To this end, an objective picture quality scale is essential for image processing.This paper analyzes human perceptual properties in detail, formulizes approximately the fundamental image disturbance factors and proposes an objective picture quality scale (PQS).As a test image, a coding error image was fed into a neural network and experiments were conducted with a method to evaluate the picture quality.Finally, the new objective picture quality scale obtained herein can estimate the mean opinion scores (MOS) of two kinds of previously untaught images whose characteristics differ greatly.