Contour Interpolation Research Articles

Breakdown of contour interpolation: Testing a multiple-contours hypothesis

Breakdown of contour interpolation: Testing a multiple-contours hypothesis

Tolerance for misalignment in contour interpolation: retinal or relational?

Tolerance for misalignment in contour interpolation: retinal or relational?

Contour interpolation: Necessary but not sufficient for the perception of interpolated contours

Contour interpolation: Necessary but not sufficient for the perception of interpolated contours

Three-dimensional contour interpolation: Testing the 90-degree constraint

Three-dimensional contour interpolation: Testing the 90-degree constraint

Do spatial factors influence the microgenesis of illusory contours?

Spatial factors such as contour curvature and support ratio influence the perceived strength of illusory contours. However, it is unknown whether these determinants of interpolative strength affect how quickly interpolated contours emerge during visual processing (microgenesis). We approached this issue using a dot localization method. Observers briefly viewed Kanizsa-type illusory shapes with varying support ratios and relative inducer orientations, as well as stimuli containing comparable spatial cues that did not give rise to illusory contours (non-IC stimuli). During the last 40 ms prior to masking, a small dot appeared somewhere between two inducers. Observers judged whether the dot appeared inside or outside of the illusory shape's perceived boundary. Dot position varied based on observer responses; two interleaved staircases produced the 83% threshold points for seeing the dot inside versus outside of the boundary. This objective paradigm revealed both the accuracy of the interpolation and the strength or precision with which the contour is perceived. Stimulus duration varied from 40 ms to 480 ms, allowing investigation of the microgenesis of contour formation. Our results indicated that observers localized a dot more accurately and precisely relative to illusory contours than relative to comparable non-IC stimuli; this difference diminished at longer durations, suggesting that the time course of illusory contour formation differs from the time course by which more cognitive strategies become useful. Second, consistent with previous data, our results suggest that all illusory contours emerge rapidly; precision reached asymptote within the first 120 ms following stimulus onset. Finally, preliminary data suggest that spatial factors affecting the subjective strength of illusory contours (curvature and support ratio) also influence the time course over which interpolation proceeds. These results will be discussed in the context of contour interpolation models.

A unified model of illusory and occluded contour interpolation

Models of contour interpolation have been proposed for illusory contour interpolation but seldom for interpolation of occluded contours. The identity hypothesis ( Kellman & Loukides, 1987; Kellman & Shipley, 1991) posits that an early interpolation mechanism is shared by interpolated contours that are ultimately perceived as either illusory or occluded. Here we propose a model of such a unified interpolation mechanism for illusory and occluded contours, building on the framework established in Heitger, von der Heydt, Peterhans, Rosenthaler, and Kubler (1998). We show that a single, neurally plausible mechanism that is consistent with the identity hypothesis also generates contour interpolations in agreement with perception for cases of transparency, self-splitting objects, interpolation with mixed boundary assignment, and “quasimodal” interpolations. Limiting cases for this local, feed-forward approach are presented, demonstrating that both early, local interpolation mechanisms and non-local scene constraints are necessary for describing the perception of interpolated contours.

WE-E-AUD A-06: Image and Dose Processing for Image Guided Adaptive Radiation Therapy and Outcome Research

Purpose: To develop a general image processing and dose computation procedure that allows for the accumulation of accurate dose distributions for purposes of both outcome research and IG‐ART (image guided adaptive radiation therapy). We applied the procedure to cone‐beam CT head‐neck cancertreatment cases, as well as Tomotherapy MVCT (mega‐voltage CT) GYN and prostate cancertreatment cases. Method and Materials: The image processing procedures include preprocessing, rigid and deformable registration, mesh‐ based structure contour propagation, and image volume composition for dose re‐computation. The dose processing includes dose recomputation on the daily CT or the composed CT volume, deforming and register the daily dose to the planning dose space, dose accumulation, evaluating of the accumulated dose against the planned dose. Accuracy of image registration is very important for the entire procedure because it determines the accuracy of all later subsequent steps. In order to improve the accuracy, we preprocessed the CTimages before the registration step by using various methods, including edge‐preserving smoothing, Gaussian lowpass smoothing, contrast enhancement, window‐level intensity transformation, and bowel gas pocket painting for abdominal regions. We used MI (mutual information) based algorithm for rigid image registration, and applied the Horn‐Schunck optical flow algorithm for deformable image registration. We used a mesh‐based algorithm for structure contour deformation, interpolation and smoothing. Results: By applying these preprocessing procedures we were able to achieve improved image registration results. The computed image deformation fields were then used to propagate the structure contours from the kVCT to the current daily CTimage, which could be used for dose deformation or re‐computation. Conclusion: We have developed a procedure of image processing and dose computation to support the accumulation of ‘true’ dose distributions. These methods could be used in both radiotherapy outcome research and adaptive radiotherapy applications. Partially supported by NIH R01 grant CA85181.

Local determinants of contour interpolation

Objects in our visual environment are perceived as integral wholes even when their retinal images are incomplete. We ask whether the perceptual precision of subjective interpolation between isolated image parts depends on the overall proportion of visible image information or rather on its geometrical arrangement. We used Varin-type subjective shapes that provide less physical stimulus information than Kanizsa-type figures because partially occluded solid inducers are replaced by partially occluded concentric arcs. We tested whether perceptual precision varies as a function of contour support, or alternatively, depends on the number of, and the distance between, line endings within the inducers. We measured performance in a probe localization task, where a small target is presented at different distances around a subjective boundary. Sensitivity, captured by the just noticeable position difference between in- and outside probes, crucially depended on the geometric arrangement of line ends in the Varin figures. This is objective evidence that the apparent subjective contour strength does not primarily depend on contour support but is determined by the number and the separation between inducers' line endings. The results suggest that neuronal mechanisms sensitive to highly localized 2D features are crucial for determining the perceived shape of visual objects.

Precision and consistency of contour interpolation

We investigated conditions under which observers can interpolate occluded contours by a single, stable, smooth contour. Observers viewed partly-occluded contours defined by linear segments and estimated the position and tangent orientation of the contour at multiple locations within the occluded region. We measured the precision and consistency of observers’ settings as indices of successful interpolation. We found that although increasing the relative offset between inducers led to a decrease in both precision and consistency, increasing turning angle affected primarily precision. We discuss conditions under which interpolation settings are consistent with a single, stable smooth contour.

Retinotopic activation in response to subjective contours in primary visual cortex

Objects in our visual environment are arranged in depth and hence there is a considerable amount of overlap and occlusion in the image they generate on the retina. In order to properly segment the image into figure and background, boundary interpolation is required even across large distances. Here we study the cortical mechanisms involved in collinear contour interpolation using fMRI. Human observers were asked to discriminate the curvature of interpolated boundaries in Kanizsa figures and in control configurations, which contained identical physical information but did not generated subjective shapes. We measured a spatially precise spin-echo BOLD signal and found stronger responses to subjective shapes than non-shapes at the subjective boundary locations, but not at the inducer locations. The responses to subjective contours within primary visual cortex were retinotopically specific and analogous to that to real contours, which is intriguing given that subjective and luminance-defined contours are physically fundamentally different. We suggest that in the absence of retinal stimulation, the observed activation changes in primary visual cortex are driven by intracortical interactions and feedback, which are revealed in the absence of a physical stimulus.

Classification images reveal spatiotemporal contour interpolation

Contour interpolation is the process whereby spatially separated object fragments (inducers) are connected on the basis of their contour relations. An important characteristic of interpolation between simultaneously presented inducers is that observers rely on interpolation regions to perform a discrimination task. However, it is unclear if the same property holds when inducers are separated in both space and time. To address this question of spatiotemporal interpolation, we had participants discriminate spatiotemporally presented “fat” and “thin” noise-corrupted figures, when the figures were stationary (Experiment 1) or moving (Experiment 2), and when the connections across vertical gaps were either real, interpolated (illusory), or absent. Classification images from both experiments showed that noise regions near interpolated boundaries affect performance comparably to when real contours appear, but very little in the absence of interpolation. The classification images also revealed information about the time course of interpolation and suggested that contour interpolation between simultaneously visible inducers may be a special case of a more general spatiotemporal contour interpolation process. 1 The following acronyms appear in this paper: RMS—root mean square; SNR—signal to noise ratio; CI—Classification image. 1

A reliable surface reconstruction system in biomedicine

For common biomedical imaging facilities, such as CT, MRI, and confocal microscopy, the acquired scans are sequential parallel sections. The object of interest in each section image can be extracted by segmentation procedure to form serial parallel planar contours. How to reconstruct a trustworthy surface from these contours is a crucial issue in biomedical 3D visualization. In this paper, we propose an automatic, fast, and reliable surface reconstruction system. An improved correspondence-determining algorithm is proposed in the system to provide more reasonable contour-correspondences than the existing algorithms. It can handle more general input data, and does not produce wrong reconstruction results. A hybrid tiling algorithm is presented to tile the corresponding contours without the requirement of a contour-matching procedure. It can also handle the branching problem without any modification. For degenerate cases and branches, intermediate contours are introduced by means of contour interpolation to enhance the reconstruction results. The surface area and volume are also calculated to facilitate the practical applications.

Mechanisms of modal and amodal interpolation.

P. J. Kellman and T. F. Shipley (1992) and P. J. Kellman, P. Garrigan, and T. F. Shipley (2005) suggested that completion of partly occluded objects and illusory objects involve the same or similar mechanisms at critical stages of contour interpolation. B. L. Anderson, M. Singh, and R. W. Fleming and B. L. Anderson (2007) presented a number of arguments against this view. The author analyzes 3 of these arguments, as well as B. L. Anderson's ecological justification for believing that these mechanisms must be very different, and suggests that their conclusions are unwarranted. The author also outlines a model consistent with the identity hypothesis and with recent physiological evidence, including a quantitative proposal for contour interpolation strength. The model suggests that V1 and V2 receive from higher visual areas feedback that modulates their responses to stimuli eliciting modal completion, amodal completion, and collinear contour facilitation. The model qualitatively explains the unstable percepts evoked by various recently devised stimuli.

The demise of the identity hypothesis and the insufficiency and nonnecessity of contour relatability in predicting object interpolation: Comment on Kellman, Garrigan, and Shipley (2005).

P. J. Kellman, P. Garrigan, and T. F. Shipley's theory of 3-dimensional object interpolation asserts that existing data, as well as logical considerations, support the view that an identical contour interpolation process underlies the interpolation of partially camouflaged and partially occluded objects (modal completion and amodal completion, respectively). Here, the author argues that recent data show that this theory is incorrect and that the logical arguments offered in support of the identity hypothesis depend on specific unverified models of the phenomena in question. Alternative explanations of these effects are developed to show that such phenomena do not logically implicate an identity hypothesis and, in some cases, provide strong evidence against the identity hypothesis. Finally, the author describes several completion phenomena that reveal that the relatability criteria embodied in Kellman et al.'s model are neither necessary nor sufficient for understanding the interpolation processes the model was designed to explain.

Filling-in models of completion: Rejoinder to Kellman, Garrigan, Shipley, and Keane (2007) and Albert (2007).

There has been a growing interest in understanding the computations involved in the processes underlying visual segmentation and interpolation in conditions of occlusion. P. J. Kellman, P. Garrigan, T. F. Shipley, and B. P. Keane and M. K. Albert defended the view that identical contour interpolation mechanisms underlie modal and amodal completion. In the current rejoinder, the author provides further psychophysical evidence against this view and argues that no physiological data support the claim that modal and amodal contours are represented identically at any stage of processing. The author also shows that the illusory glass surfaces that Kellman et al. and Albert upheld as evidence against his arguments about luminance constraints in completion are explained by theoretical principles that he has previously articulated, and variants of these illusions receive no explanation within either of the models Kellman et al. and Albert propose. The author shows that the principles needed to explain these percepts embody fundamental asymmetries in the way that relative depth shapes segmentation and interpolation processes and that models of completion that lack these constraints--such as P. J. Kellman, P. Garrigan, and T. F. Shipley's and M. K. Albert's --cannot account for a host of documented completion phenomena.

Polygon interpolation for serial cross sections

In this paper, a new technique for contour interpolation between slices is presented. We assumed that contour interpolation is equivalent to the interpolation of a polygon that approximates the object shape. The location of each polygon vertex is characterized by a set of parameters. Polygon interpolation can be performed on these parameters. These interpolated parameters are then used to reconstruct the vertices of the new polygon. Finally, the contour is approximated from this polygon using a cubic spline interpolation. This new technique takes into account the shape, the translation, the size, and the orientation of the object's contours. A comparison with regular shape-based interpolation is made on several object contours. The preliminary results show that this new method yields a better contour and is computationally more efficient than shape-based interpolation. This technique can be applied to gray-level images too. The interpolation result of an MR image does not show artifact of intermediate substance commonly seen in a typical linear gray-level interpolation.

A theory of dynamic occluded and illusory object perception.

Humans see whole objects from input fragmented in space and time, yet spatiotemporal object perception is poorly understood. The authors propose the theory of spatiotemporal relatability (STR), which describes the visual information and processes that allow visible fragments revealed at different times and places, due to motion and occlusion, to be assembled into unitary perceived objects. They present a formalization of STR that specifies spatial and temporal relations for object formation. Predictions from the theory regarding conditions that lead to unit formation were tested and confirmed in experiments with dynamic and static, occluded and illusory objects. Moreover, the results support the identity hypothesis of a common process for amodal and modal contour interpolation and provide new evidence regarding the relative efficiency of static and dynamic object formation. STR postulates a mental representation, the dynamic visual icon, that briefly maintains shapes and updates positions of occluded fragments to connect them with visible regions. The theory offers a unified account of interpolation processes for static, dynamic, occluded, and illusory objects.

Dynamic texture spreading: probing the mechanisms of surface interpolation

Dynamic texture spreading is a filling-in phenomenon where a colored pattern perceptually spreads onto an area confined by virtual contours in a multi-aperture motion display. The spreading effect is qualitatively similar to static texture spreading but widely surpasses it in strength, making it particularly suited for quantitative studies of visual interpolation processes. We first carried out two experiments to establish with objective tasks that texture spreading is a genuine representation of surface qualities and thus goes beyond mere contour interpolation. Two subsequent experiments serve to relate the phenomenon to ongoing discussions about potentially responsible mechanisms for spatiotemporal integration. With a phenomenological method, we examined to what extent simple sensory persistence might be causally involved in the effect under consideration. Most of our findings are consistent with the idea of sensory persistence, and indicate that information fragments are integrated over a time window of about 100 to 180 ms to form a complete surface representation.

3-D Interpolation in Object Perception: Evidence From an Objective Performance Paradigm.

Object perception requires interpolation processes that connect visible regions despite spatial gaps. Some research has suggested that interpolation may be a 3-D process, but objective performance data and evidence about the conditions leading to interpolation are needed. The authors developed an objective performance paradigm for testing 3-D interpolation and tested a new theory of 3-D contour interpolation, termed 3-D relatability. The theory indicates for a given edge which orientations and positions of other edges in space may be connected to it by interpolation. Results of 5 experiments showed that processing of orientation relations in 3-D relatable displays was superior to processing in 3-D nonrelatable displays and that these effects depended on object formation. 3-D interpolation and 3-D relatabilty are discussed in terms of their implications for computational and neural models of object perception, which have typically been based on 2-D-orientation-sensitive units.

Contour curvature polarity and surface interpolation

Contour curvature polarity (i.e., concavity/convexity) is recognized as an important factor in shape perception. However, current interpolation models do not consider it among the factors that modulate the trajectory of amodally-completed contours. Two hypotheses generate opposite predictions about the effect of contour polarity on surface interpolation. Convexity advantage: if convexities are preferred over concavities, contours of convex portions should be more extrapolated than those of concave portions. Minimal area: if the area of amodally-completed surfaces tends to be minimized, contours of convex portions should be less extrapolated than contours of concave portions. We ran three experiments using two methods, simultaneous length comparison and probe localization, and different displays (pictures vs. random dot stereograms). Results indicate that contour polarity affects the amodally-completed angles of regular and irregular surfaces. As predicted by the minimal area hypothesis, image contours are less extrapolated when the amodal portion is convex rather than concave. The field model of interpolation [Fantoni, C., & Gerbino, W. (2003). Contour interpolation by vector-field combination. Journal of Vision, 3, 281–303. Available from http://journalofvision.org/3/4/4/] has been revised to take into account surface-level factors and to explain area minimization as an effect of surface support ratio.