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We can see things in three dimensions because the visual system re-constructs the three-dimensional (3D) configurations of objects from their two-dimensional (2D) images projected onto the retinas. The purpose of this paper is to give an overview of the psychological background and recent physiological findings concerning three-dimensional vision. Psychophysical and computational studies have suggested that in the visual system the 3D surface orientation is first estimated independently from individual depth cues--such as binocular disparity, as well as various monocular cues including texture gradients--and then the information from these different depth cues is integrated to construct a generalized representation of the 3D surface geometry. Neurons involved in low-level disparity processing, or the detection of local absolute disparity, were found mainly in the occipital cortex, whereas neurons involved in high-level disparity processing, or the reconstruction of 3D surface orientation through the computation of disparity gradients, were found mainly in the parietal area caudal intraparietal sulcus (CIP). Neurons sensitive to texture gradients, which is one of the major monocular cues, were also found in CIP. The majority of these neurons were sensitive to disparity gradients as well, suggesting their involvement in the computation of 3D surface orientation. In CIP, neurons sensitive to multiple depth cues were widely distributed together with those sensitive to a specific depth cue, suggesting CIP's involvement in the integration of depth information from different sources. In addition, human and monkey imaging studies have indicated convergence of multiple depth cues in CIP. These neurophysiological findings suggest that CIP plays a critical role in 3D vision by constructing a generalized representation of the 3D surface geometry of objects.
PSYCHOMETRIC FUNCTION: According to the European standard EN ISO 8596 the Landolt-C in 8 different orientations has to be used to measure visual acuity. With decreasing size of the Landolt-C the hit rate declines from 100% to the chance level of 12.5%. This gradual transition is described by the "psychometric function". The steepest point of the psychometric function is in the middle between 100 and 12.5, i.e., at 56.25%. This point of the psychometric function (approximated by 5 of 8 Landolt-Cs) has been selected as the threshold for visual acuity, because it is there that the visual acuity is influenced least by (incidental) fluctuations. The subject has to answer by forced choice; a response like "I cannot detect anything" is not acceptable. "NORMAL" VISUAL ACUITY: Cannot be assigned to a certain value, like 1.0 or 6/6. With the standard test procedure, visually healthy, young subjects achieve a visual acuity of about 2.0 or 12/6, while in senior subjects 0.5 (3/6) may be "normal". AVERAGING VISUAL ACUITY: Logarithmic, not arithmetic, scaling of visual acuity approximates the perceptual metric. Consequently, visual acuity values may not be averaged arithmetically. Instead, three steps are required: all values have to be converted to logarithms, then averaged, and finally the average can be reconverted. Geometric averaging is equivalent. "MINIMUM ANGLE OF RESOLUTION" NOT NECESSARY: MAR is the reciprocal of visual acuity. In many studies, clinical outcome has been assessed using log(MAR). Though statistically correct, this term is unnecessary, as log(acuity) has identical statistical properties. Furthermore, log(MAR) is contra-intuitive as its value becomes smaller when vision improves. COMPUTER-ASSISTED INSTRUMENTATION: Facilitates complying with the EN ISO 8596. For instance, the Freiburg Visual Acuity Test relieves the examiner from observing whether 5 responses have been correct, and that not more than 8 tests are given per level.
Right-handed subjects participated in a visual half-field experiment using "clock" stimuli. For the Categorical task, subjects indicated whether the long and short hands of a clock were above or below the horizontal midline of the dial. For the Coordinate task, they indicated whether the long and short hands of a clock formed an angle that is more or less than 60 degrees. For both tasks, clock stimuli were either analog clocks (Visual version) or digital clocks from which subjects generated images of analog clocks (Imagery version). The results indicated that for both the Visual and Imagery versions, there was a nonsignificant trend toward a left hemisphere advantage in the Categorical task, whereas there was a significant right hemisphere advantage in the Coordinate task. Implications of the results were discussed from the viewpoints of task factors in hemispheric processing of visual imagery, Kosslyn's (1987, 1994) computational model of vision and visual imagery, and vision/imagery isomorphism.
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Color vision abnormalities indicated by the Farnsworth-Munsell 100-hue Color Vision Tests (FM-100) were analyzed by computer to better characterize and group congenital and acquired color vision disorders and to help establish statistically significant diagnostic criteria. Standard evaluation of the FM-100 is by axis and error score calculations. A method has been established for computer-averaging many tests from patients with the same color abnormalities determined by history, standard FM-100 and Nagel anomaloscope. The computer calculated an average error score and standard deviation for each of the 85 color caps. Every time a new patient was evaluated for color vision abnormality, his score was compared with averaged tests with common diagnoses, by calculating distance scores. The averaged test with the lowest distance score consistently tended to coincide with the diagnosis. An analysis of 130 FM-100 color tests found technician-calculated error scores to be incorrect, although usually minor, in 40% of the tests. The computer-calculated axes agreed well with the technician's estimates. The distance scores predicted the diagnosis accurately 89% of the time. Many errors were due to the small number of protanopes averaged and inability to distinguish trichromats from dichromats.
This study examined the variability in movement end points in a task in which human subjects reached to targets in different locations on a horizontal surface. The primary purpose was to determine whether patterns in the variable errors would reveal the nature and origin of the coordinate system in which the movements were planned. Six subjects moved a hand-held cursor on a digitizing tablet. Target and cursor positions were displayed on a computer screen, and vision of the hand and arm was blocked. The screen cursor was blanked during movement to prevent visual corrections. The paths of the movements were straight and thus directions were largely specified at the onset of movement. The velocity profiles were bell-shaped, and peak velocities and accelerations were scaled to target distance, implying that movement extent was also programmed in advance of the movement. The spatial distributions of movement end points were elliptical in shape. The major axes of these ellipses were systematically oriented in the direction of hand movement with respect to its initial position. This was true for both fast and slow movements, as well as for pointing movements involving rotations of the wrist joint. Using principal components analysis to compute the axes of these ellipses, we found that the eccentricity of the elliptical dispersions was uniformly greater for small than for large movements: variability along the axis of movement, representing extent variability, increased markedly but nonlinearly with distance. Variability perpendicular to the direction of movement, which results from directional errors, was generally smaller than extent variability, but it increased in proportion to the extent of the movement. Therefore, directional variability, in angular terms, was constant and independent of distance. Because the patterns of variability were similar for both slow and fast movements, as well as for movements involving different joints, we conclude that they result largely from errors in the planning process. We also argue that they cannot be simply explained as consequences of the inertial properties of the limb. Rather they provide evidence for an organizing mechanism that moves the limb along a straight path. We further conclude that reaching movements are planned in a hand-centered coordinate system, with direction and extent of hand movement as the planned parameters. Since the factors which influence directional variability are independent of those that influence extent errors, we propose that these two variables can be separately specified by the brain.
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Recently, Marr & Poggio (1979) presented a theory of human stereo vision. An implementation of that theory is presented, and consists of five steps. (i) The left and right images are each filtered with masks of four sizes that increase with eccentricity; the shape of these masks is given by delta 2G, the Laplacian of a Gaussian function. (ii) Zero crossings in the filtered images are found along horizontal scan lines. (iii) For each mask size, matching takes place between zero crossings of the same sign and roughly the same orientation in the two images, for a range of disparities up to about the width of the mask's central region. Within this disparity range, it can be shown that false targets pose only a simple problem. (iv) The output of the wide masks can control vergence movements, thus causing small masks to come into correspondence. In this way, the matching process gradually moves from dealing with large disparities at a low resolution to dealing with small disparities at a high resolution. (v) When a correspondence is achieved, it is stored in a dynamic buffer, called the 2 1/2-dimensional sketch. To support the adequacy of the Marr-Poggio model of human stereo vision, the implementation was tested on a wide range of stereograms from the human stereopsis literature. The performance of the implementation is illustrated and compared with human perception. Also statistical assumptions made by Marr & Poggio are supported by comparison with statistics found in practice. Finally, the process of implementing the theory has led to the clarification and refinement of a number of details within the theory; these are discussed in detail.
OBJECTIVE: To investigate the reported increase in the expression of the glucose transporter GLUT-1 in borderline and malignant ovarian epithelial tumors and its relationship to prognosis. STUDY DESIGN: In this study, areas in which immunohistochemical membranous staining with GLUT-1 were most evident were selected, and the proportions of GLUT-1 expression in 46 benign, 11 borderline and 42 malignant cases of ovarian epithelial tumors were determined quantitatively with a computer and Zeiss Vision KS 400 3.0 (Göttingen, Germany) for Windows (Microsoft, Redmond, Washington, U.S.A.) image analysis. RESULTS: GLUT-1 expression was determined in all borderline tumors (11 of 11) and in 97.6% of malignant tumors (41 of 42). No GLUT-1 expression was observed in benign tumors. The intensity of GLUT-1 staining was lower in borderline tumors than in malignant cases. This was statistically significant (p = 0.005). As differentiation in malignant tumors increased, proportions of GLUT-1 expression showed a relative increase, but this difference was not statistically significant (p = 0.68). CONCLUSION: When GLUT-1 expression in borderline and malignant ovarian epithelial tumors was analyzed against prognosis, no statistically significant difference was identified. Assessment of GLUT-1 expression using the image analysis program was more reliable, with higher reproducibility than in previous studies.
Part structure and articulation are of fundamental importance in computer and human vision. We propose using the inner-distance to build shape descriptors that are robust to articulation and capture part structure. The inner-distance is defined as the length of the shortest path between landmark points within the shape silhouette. We show that it is articulation insensitive and more effective at capturing part structures than the Euclidean distance. This suggests that the inner-distance can be used as a replacement for the Euclidean distance to build more accurate descriptors for complex shapes, especially for those with articulated parts. In addition, texture information along the shortest path can be used to further improve shape classification. With this idea, we propose three approaches to using the inner-distance. The first method combines the inner-distance and multidimensional scaling (MDS) to build articulation invariant signatures for articulated shapes. The second method uses the inner-distance to build a new shape descriptor based on shape contexts. The third one extends the second one by considering the texture information along shortest paths. The proposed approaches have been tested on a variety of shape databases, including an articulated shape data set, MPEG7 CE-Shape-1, Kimia silhouettes, the ETH-80 data set, two leaf data sets, and a human motion silhouette data set. In all the experiments, our methods demonstrate effective performance compared with other algorithms.
We present a set of texture parameters that correspond to perceptual properties of visual texture. For machine vision or a computer interface, it is important that the computational measurements of texture correspond well to the perceptual properties. To understand the mechanism of our visual system, it is important to know how we extract or characterize information for texture perception. In this study, we show that the autocorrelation function (ACF) analysis provides useful measures for representing three salient perceptual properties of texture: contrast, coarseness, and regularity. The validity of the ACF analysis was examined by comparing the calculated factors to the subjective scores collected for various kinds of natural textures. The effectiveness of the analysis depends on the structure of the estimated ACF. When a texture has a harmonic structure, the estimated ACF has periodical peaks corresponding to the periods of the texture. Both perceived coarseness and regularity are strongly related to these peaks in the ACF. However, the estimated ACF does not have a periodical structure when the texture is random. In this case, the texture coarseness and regularity are represented by the decay rate of the ACF.
To investigate whether or not adaptation to second-order motion can cause changes in perceived speed, measurements of perceived speed were obtained for two varieties of motion: (i) contrast-modulated two-dimensional static noise (second-order motion); and (ii) luminance-modulated noise (first-order motion). The test stimulus (either first-order or second-order) was presented to one side of a central fixation spot and a comparison stimulus (always first-order) was simultaneously presented on the opposite side. The observer's task was to indicate which of the two motion stimuli appeared to drift faster. The perceived speed of the test stimulus was measured with and without prior adaptation to motion on one side of the fixation spot only (that of the test stimulus). The modulation depth of the adaptation stimulus was always half that of the test stimulus and all test patterns were equated for visibility. The pattern of results for second-order motion was similar to that for first-order motion. Typically, adaptation reduced perceived speed, particularly when the adaptation speed was faster than the test speed. However, when the adaptation speed was low relative to the test speed, increases in perceived speed were found. Cross-over adaptation effects between first-order and second-order motion were also observed. Robust velocity aftereffects were found for second-order motion when the noise was dynamic or was high-pass filtered, suggesting that first-order (luminance) artifacts were not responsible for the velocity aftereffects observed. We conclude that the perceived speeds of first-order and second-order motion appear to be encoded in human vision using similar computational principles (but not necessarily utilizing the same mechanism), since the same pattern of results was found for the two varieties of motion.
MRI is noninvasive and generates clear images, giving it great potential as a diagnostic instrument. However, current methods of image analysis are too time-consuming for dynamic systems such as the cardiovascular system. Since dynamic imagery generate a huge number of images, a computer aided machine vision diagnostic tool is essential for implementing MRI-based measurement. In this paper, a wavelet-based image technique is applied to enhance left ventricular endocardial and epicardial profiles as the preprocessor for a dynamic programming-based automatic border detection algorithm. Statistical tests are conducted to verify the performance of the enhancement technique by comparing borders manually drawn with 1. borders generated from the enhanced images, and 2. borders generated for the original images.
The past year has seen great advances in the use of functional magnetic resonance imaging (fMRI) to study the functional organization of the human visual cortex, to measure the neuronal correlates of visual perception, and to test computational theories of vision. Activity in particular visual brain areas, as measured with fMRI, has been found to correlate with psychophysical performance, with visual attention, and with subjective perceptual experience.
Chronic decreases in brain cholinergic functions due to intraventricular administration of the neurotoxin AF64A were accompanied by increases in the latent period of locating an invisible platform during training of rats in a Morris water test, as compared with control sham-operated animals. Recordings of the animals' movement trajectories using a video camera along with an original computer program (Behavioral Vision) showed that administration of 17beta-estradiol and its synthetic analog J-861 (0.2 mg/kg p.o. daily for seven days before and 10 days after single intraventricular injections of AF64A) improved learning. The directivity of platform search trajectories was assessed quantitatively using a new parameter--trajectory straightness. Introduction of the "passive swimming" parameter allowed periods of immobility in water to be identified within the total latent period in animals after administration of AF64A; 17beta-estradiol but not J-861 "eliminated" these periods. The new parameters (especially trajectory straightness) allowed the ability to learn to be discriminated from decreases in mobility, including mobility losses due to study agents, in the Morris water test.
Cysticercosis of the optic nerve is an extremely rare entity and only seven cases have been reported in the world literature. A case of optic nerve cysticercosis in a 25-year-old woman is reported, along with a review of literature. The patient presented with two episodes of pain, diminution of vision and proptosis. Computed tomography and ultrasonography revealed an intraneural cyst with scolex in the retrobulbar portion of the optic nerve. A positive enzyme-linked immunosorbent assay test for cysticercosis further confirmed the diagnosis. Medical therapy in the form of oral albendazole and steroids resulted in complete resolution of the cyst, with few visual sequelae.
In many computational approaches to vision it has been emphasised that object recognition involves the encoding of view-independent descriptions prior to matching to a stored object model, thus enabling objects to be identified across different retinal projections. In contrast, neurophysiological studies suggest that image descriptions are matched to less abstract, view-specific representations, resulting in more efficient access to stored object knowledge for objects presented from a view similar to a stored viewpoint. Evidence favouring a primary role for view-specific object descriptions in object recognition is reported. In a series of experiments employing line drawings of familiar objects, the effects of depth rotation upon the efficiency of object recognition were investigated. Subjects were required to identify an object from a sequence of very briefly presented pictures. The results suggested that object recognition is based upon the matching of image descriptions to view-specific stored representations, and that priming effects under sequential viewing conditions are strongly influenced by the visual similarity of different views of objects.