A Psychophysical Oriented Saliency Map Prediction Model

Visual attention is one of the most significant characteristics for selecting and understanding the outside redundancy world. The human vision system cannot process all information simultaneously, due to the visual information bottleneck. In order to reduce the redundant input of visual information, the human visual system mainly focuses on dominant parts of scenes. This is commonly known as visual saliency map prediction. This paper proposed a new psychophysical saliency prediction architecture, WECSF, inspired by multi-channel model of visual cortex functioning in humans. The model consists of opponent color channels, wavelet transform, wavelet energy map, and contrast sensitivity function for extracting low-level image features and providing maximum approximation to the human visual system. The proposed model is evaluated using several datasets, including the MIT1003, MIT300, TORONTO, SID4VAM, and UCF Sports datasets. We also quantitatively and qualitatively compare the saliency prediction performance with that of other state-of-the-art models. Our model achieved strongly stable and better performance with different metrics on nature images, psychophysical synthetic images and dynamic videos. Additionally, we found that Fourier and spectral-inspired saliency prediction models outperformed other state-of-the-art non-neural network and even deep neural network models on psychophysical synthetic images, it can be explained and supported the Fourier Vision Hypothesis. Finally, the proposed model could be used as a computational model of primate vision system and help us understand mechanism of vision system

Low-level spatiochromatic grouping for saliency estimation

We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Designing pictorial stimuli for perceptual image difference experiments

Imaging system development often involves impact assessment of design choices. For systems that generate images for human consumption, such as cameras and displays, the effect of design decisions are often evaluated using `real-world\u27 images. System changes can have complicated effects on pictorial images that do not, as yet, have specified instrumental measurement methods. Consequently, human observers are often used in image quality assessment. However, human observers can react differently to complex pictorial stimuli both between observers and for a single observer over the course of a lengthy experiment. In an experimental setting, pictorial scenes present a greater opportunity than do uniform patches for observers\u27 individual differences to significantly impact the process. This study was conducted to increase the understanding of the optimal design of pictorial stimuli for more effective and efficient perceptual experiments. The goals of this dissertation were to: 1. Understand the impact of image content on visual attention and the consistency of image comparison experimental results 2. Understand how visual attention changes with successive viewing of pictorial images 3. Apply this understanding to develop guidelines for pictorial target design for perceptual image comparison experiments To achieve these objectives, a series of experiments were conducted to evaluate the impact of pictorial scene complexity on fixation and experimental response consistency. For these experiments, scenes exhibiting a range of perceived complexity were required. To select appropriate scenes, the concept of what constitutes a complex image was first considered. Experiment I was conducted to evaluate the number of areas perceived to be important in a variety of scenes. Observers were asked to identify the important areas of pictorial scenes. The scenes were also electronically segmented. The results from Experiment I were used to select scenes that provided a range of complexity for stimuli in Experiment II. This test examined the impact of image complexity on observer viewing behavior. Along with evaluating eye movements, observers were asked to describe the test scenes using up to five keywords. The results of Experiments I & II indicate that perceptual methods, segmentation, and eye-tracking generally provided consistent results with regard to image complexity. The exceptions involved issues of scale such that scenes viewed from afar blended into one significant object while one object viewed up close lacked a point of focus. The results of Experiment II were used to generate a proposal for guidelines for designing pictorial stimuli for image comparison experiments. Using these guidelines, scenes were selected and tested in Experiment III. The fixation consistency results of this experiment were generally as expected. However, fixation consistency did not always equate to experimental response consistency. Along with scene complexity, the image modifications (global versus local) and the difficulty of making the image equivalency decisions played a role in the experimental response as well. The results of Experiment III were used to confirm and augment the proposed guidelines. The guidelines developed in this study will benefit those conducting perceptual experiments with pictorial stimuli. Specific examples include color reproduction, perceptual color standards, and image equivalency research. A better understanding of what makes images equivalent may be useful in developing automated approaches to measuring image quality. And the guidelines may be useful in the improvement of the quality of images themselves. Fredembach (2011) has proposed that perceived image quality can be improved by increasing the perceived saliency of the main subject matter. These guidelines, including the use of blur, will be helpful in achieving this aim