Zygmunt Pizlo

The function of visual search and memory in sequential looking tasks

UNLABELLED Eye and head movements were recorded as unrestrained subjects tapped or only looked at nearby targets. Scanning patterns were the same in both tasks: subjects looked at each target before tapping it; visual search had similar speeds and gaze-shift accuracies. Looking, however, took longer and, unlike tapping, benefitted little from practice. Looking speeded up more than tapping when memory load was reduced: memory was more efficient during tapping. CONCLUSION eye movements made when only looking are different from those made when tapping. Visual search functions as a separate process, incorporated into both tasks: it can be used to improve performance when memory load is heavy.

Camouflage and visual perception

How does an animal conceal itself from visual detection by other animals? This review paper seeks to identify general principles that may apply in this broad area. It considers mechanisms of visual encoding, of grouping and object encoding, and of search. In most cases, the evidence base comes from studies of humans or species whose vision approximates to that of humans. The effort is hampered by a relatively sparse literature on visual function in natural environments and with complex foraging tasks. However, some general constraints emerge as being potentially powerful principles in understanding concealment—a ‘constraint’ here means a set of simplifying assumptions. Strategies that disrupt the unambiguous encoding of discontinuities of intensity (edges), and of other key visual attributes, such as motion, are key here. Similar strategies may also defeat grouping and object-encoding mechanisms. Finally, the paper considers how we may understand the processes of search for complex targets in complex scenes. The aim is to provide a number of pointers towards issues, which may be of assistance in understanding camouflage and concealment, particularly with reference to how visual systems can detect the shape of complex, concealed objects.

The traveling salesman problem: A hierarchical model

Our review of prior literature on spatial information processing in perception, attention, and memory indicates that these cognitive functions involve similar mechanisms based on a hierarchical architecture. The present study extends the application of hierarchical models to the area of problem solving. First, we report results of an experiment in which human subjects were tested on a Euclidean traveling salesman problem (TSP) with 6 to 30 cities. The subject’s solutions were either optimal or near-optimal in length and were produced in a time that was, on average, a linear function of the number of cities. Next, the performance of the subjects is compared with that of five representative artificial intelligence and operations research algorithms, that produce approximate solutions for Euclidean problems. None of these algorithms was found to be an adequate psychological model. Finally, we present a new algorithm for solving the TSP, which is based on a hierarchical pyramid architecture. The performance of this new algorithm is quite similar to the performance of the subjects.

Automated video program summarization using speech transcripts

Compact representations of video data greatly enhances efficient video browsing. Such representations provide the user with information about the content of the particular sequence being examined while preserving the essential message. We propose a method to automatically generate video summaries using transcripts obtained by automatic speech recognition. We divide the full program into segments based on pause detection and derive a score for each segment, based on the frequencies of the words and bigrams it contains. Then, a summary is generated by selecting the segments with the highest score to duration ratios while at the same time maximizing the coverage of the summary over the full program. We developed an experimental design and a user study to judge the quality of the generated video summaries. We compared the informativeness of the proposed algorithm with two other algorithms for three different programs. The results of the user study demonstrate that the proposed algorithm produces more informative summaries than the other two algorithms

Curve detection in a noisy image.

In this paper we propose a new theory of the Gestalt law of good continuation. In this theory perceptual processes are modeled by an exponential pyramid algorithm. To test the new theory we performed three experiments. The subjects task was to detect a target (a set of dots arranged along a straight or curved line) among background dots. Detectability was high when: (a) the target was long; (b) the density of target dots relative to the density of background dots was large; (c) the local change of angle was small along the entire line; (d) local properties of the target were known to the subject. These results are consistent with our new model and they contradict prior models.

A theory of shape constancy based on perspective invariants.

Shape constancy refers to the phenomenon in which the percept of the shape of a given object remains constant despite changes in the shape of the objects retinal image. The phenomenon of shape constancy is considered from historical, theoretical and empirical perspectives in this paper. First, four prior theories are discussed; specifically, (1) Helmholtzian theory, which assumes that shape constancy is achieved by taking an objects orientation into account, (2) Gestalt theory, which assumes that shape constancy involves a relationship between the perceived shape and perceived orientation of an object, (3) Gibsonian theory, which assumes that shape constancy is based on projective invariants and (4) multiple view theory, which assumes that shape constancy is achieved by memorizing a large set of different views of the object. It is shown, by an analysis of the prior literature, that none of these theories can actually explain the phenomenon of shape constancy. A new theory, which is based on new perspective invariants of a flat shape, is then proposed. The new Perspective Invariants Theory can account for all prior shape constancy experiments. New experiments, testing predictions of the Perspective Invariants Theory are then described. These experiments showed that: (1) a novel shape can be matched with its single perspective image in the absence of depth cues, (2) perceptual processing of shape is impaired when the range of possible values of tilt is wide, (3) perceptual processing of shape is not affected by the width of the range of possible values of slant. These results support predictions of Perspective Invariants Theory.

TRAVELING SALESMAN PROBLEM: A FOVEATING PYRAMID MODEL

We tested human performance on the Euclidean Traveling Salesman Problem using problems with 6–50 cities. Results confirmed our earlier findings that: (a) the time of solving a problem is proportional to the number of cities, and (b) the solution error grows very slowly with the number of cities. We formulated a new version of a pyramid model. The new model has an adaptive spatial structure, and it simulates visual acuity and visual attention. Specifically, the model solves the E-TSP problem sequentially by moving attention from city to city, the same way human subjects do. The model includes a parameter representing the magnitude of local search. This parameter allows modeling individual differences among the subjects. The computational complexity of the current implementation of the model is O(n 2 ), but this can most likely be improved to O[nlog(n)]. Simulation experiments demonstrated psychological plausibility of the new model.

Vision pyramids that do not grow too high

In irregular pyramids, their vertical structure is not determined beforehand as in regular pyramids. We present three methods, all based on maximal independent sets from graph theory, with the aim to simulate the major sampling properties of the regular counterparts: good coverage of the higher resolution level, not too large sampling gaps and, most importantly, the resulting height, e.g. the number of levels to reach the apex. We show both theoretically and experimentally that the number of vertices can be reduced by a factor of 2.0 at each level. The plausibility of log (diameter) pyramids is supported by psychological and psychophysical considerations. Their technical relevance is demonstrated by enhancing appearance-based object recognition. An irregular pyramid hypothesis generation for robust PCA through top-down attention mechanisms achieves higher speed and quality than regular pyramids and non-pyramidal approaches.

Image quality assessment with a gabor pyramid model of the human visual system

Reliable image quality assessments are necessary for evaluating digital imaging methods (halftoning techniques) and products (printers, displays). Typically the quality of the imaging method or product is evaluated by comparing the fidelity of an image before and after processing by the imaging method or product. It is well established that simple approaches like mean squared error do not provide meaningful measures of image fidelity. A number of image fidelity metrics have been developed whose goal was to predict the amount of differences that would be visible to a human observer. In this paper we outline a new model of the human visual system (HVS) and show how this model can be used in image quality assessment. Our model departs from previous approaches in three ways: (1) We use a physiologically and psychophysically plausible Gabor pyramid to model a receptive field decomposition; (2) We use psychophysical experiments that directly assess the percept we wish to model; and (3) We model discrimination performance by using discrimination thresholds instead of detection thresholds. The first psychophysical experiment tested the visual systems sensitivity as a function of spatial frequency, orientation, and average luminance. The second experiment tested the relation between contrast detection and contrast discrimination.

Shape constancy from novel views

Prior experiments on shape constancy from novel views are inconclusive: Some show that shapes of objects can be recognized reliably from novel views, whereas others show just the opposite. Our analysis of prior results suggests that shape constancy from novel views is reliable when the object has properties that constrain its shape: The object has volumetric primitives, it has surfaces, it is symmetrical, it is composed of geons, its contours are planar, and its images provide useful topological information about its three-dimensional structure. To test the role of some of these constraints, we performed a set of experiments. Solid shapes (polyhedra) were shown on a computer monitor by means of kinetic depth effect. Experiment 1 showed that shape constancy can be reliably achieved when a polyhedron is represented by its contours (most of the constraints are present), but not when it is represented by vertices or by a polygonal line connecting the vertices in a random order (all the constraints are absent). Experiments 2 and 3 tested the role of individual constraints. Results of these experiments show that shape constancy from novel views is reliable when the object has planar contours and when the shapes of the contours together with topological information about the relations among the contours constrain the possible interpretations of the shape. Symmetry of the object and the topological stability of its image also contribute to shape constancy.