Browsing by Subject "Structure from motion"

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Open Access
Dynamic dot displays reveal material motion network in the human brain
(Elsevier BV, 2021-03) Schmid, A. C.; Boyacı, Hüseyin; Doerschner,Katja
There is growing research interest in the neural mechanisms underlying the recognition of material categories and properties. This research field, however, is relatively more recent and limited compared to investigations of the neural mechanisms underlying object and scene category recognition. Motion is particularly important for the perception of non-rigid materials, but the neural basis of non-rigid material motion remains unexplored. Using fMRI, we investigated which brain regions respond preferentially to material motion versus other types of motion. We introduce a new database of stimuli – dynamic dot materials – that are animations of moving dots that induce vivid percepts of various materials in motion, e.g. flapping cloth, liquid waves, wobbling jelly. Control stimuli were scrambled versions of these same animations and rigid three-dimensional rotating dots. Results showed that isolating material motion properties with dynamic dots (in contrast with other kinds of motion) activates a network of cortical regions in both ventral and dorsal visual pathways, including areas normally associated with the processing of surface properties and shape, and extending to somatosensory and premotor cortices. We suggest that such a widespread preference for material motion is due to strong associations between stimulus properties. For example viewing dots moving in a specific pattern not only elicits percepts of material motion; one perceives a flexible, non-rigid shape, identifies the object as a cloth flapping in the wind, infers the object's weight under gravity, and anticipates how it would feel to reach out and touch the material. These results are a first important step in mapping out the cortical architecture and dynamics in material-related motion processing.
Open Access
Effects of surface reflectance and 3D shape on perceived rotation axis
(Association for Research in Vision and Ophthalmology, 2013) Doerschner, K.; Yilmaz, O.; Kucukoglu, G.; Fleming, R. W.
Surface specularity distorts the optic flow generated by a moving object in a way that provides important cues for identifying surface material properties (Doerschner, Fleming et al., 2011). Here we show that specular flow can also affect the perceived rotation axis of objects. In three experiments, we investigate how threedimensional shape and surface material interact to affect the perceived rotation axis of unfamiliar irregularly shaped and isotropic objects. We analyze observers' patterns of errors in a rotation axis estimation task under four surface material conditions: shiny, matte textured, matte untextured, and silhouette. In addition to the expected large perceptual errors in the silhouette condition, we find that the patterns of errors for the other three material conditions differ from each other and across shape category, yielding the largest differences in error magnitude between shiny and matte, textured isotropic objects. Rotation axis estimation is a crucial implicit computational step to perceive structure from motion; therefore, we test whether a structure from a motion-based model can predict the perceived rotation axis for shiny and matte, textured objects. Our model's predictions closely follow observers' data, even yielding the same reflectance-specific perceptual errors. Unlike previous work (Caudek & Domini, 1998), our model does not rely on the assumption of affine image transformations; however, a limitation of our approach is its reliance on projected correspondence, thus having difficulty in accounting for the perceived rotation axis of smooth shaded objects and silhouettes. In general, our findings are in line with earlier research that demonstrated that shape from motion can be extracted based on several different types of optical deformation (Koenderink & Van Doorn, 1976; Norman & Todd, 1994; Norman, Todd, & Orban, 2004; Pollick, Nishida, Koike, & Kawato, 1994; Todd, 1985).
Open Access
Object rigidity and reflectivity identification based on motion analysis
(IEEE, 2010) Zang, D.; Schrater P.R.; Doerschner, Katja
Rigidity and reflectivity are important properties of objects, identifying these properties is a fundamental problem for many computer vision applications like motion and tracking. In this paper, we extend our previous work to propose a motion analysis based approach for detecting the object's rigidity and reflectivity. This approach consists of two steps. The first step aims to identify object rigidity based on motion estimation and optic flow matching. The second step is to classify specular rigid and diffuse rigid objects using structure from motion and Procrustes analysis. We show how rigid bodies can be detected without knowing any prior motion information by using a mutual information based matching method. In addition, we use a statistic way to set thresholds for rigidity classification. Presented results demonstrate that our approach can efficiently classify the rigidity and reflectivity of an object. © 2010 IEEE.
Open Access
Rapid inference of object rigidity and reflectance using optic flow
(Springer, Berlin, Heidelberg, 2009) Zang, D.; Doerschner, Katja; Schrater P.R.
Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object's shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity. We show that it is possible to detect rigid object motion for both specular and diffuse reflective surfaces using only optic flow, and that flow can distinguish specular and diffuse motion for rigid objects. Unlike nonrigid objects, optic flow fields for rigid moving surfaces are constrained by a global transformation, which can be detected using an optic flow matching procedure across time. In addition, using a Procrustes analysis of structure from motion reconstructed 3D points, we show how to classify specular from diffuse surfaces. © 2009 Springer Berlin Heidelberg.
Open Access
Specular motion and 3D shape estimation
(Association for Research in Vision and Ophthalmology Inc., 2017) Dövencioğlu, D. N.; Ben-Shahar, O.; Barla, P.; Doerschner, K.
Dynamic visual information facilitates three-dimensional shape recognition. It is still unclear, however, whether the motion information generated by moving specularities across a surface is congruent to that available from optic flow produced by a matte-textured shape. Whereas the latter is directly linked to the firstorder properties of the shape and its motion relative to the observer, the specular flow, the image flow generated by a specular object, is less sensitive to the object's motion and is tightly related to second-order properties of the shape. We therefore hypothesize that the perceived bumpiness (a perceptual attribute related to curvature magnitude) is more stable to changes in the type of motion in specular objects compared with their matte-textured counterparts. Results from two twointerval forced-choice experiments in which observers judged the perceived bumpiness of perturbed spherelike objects support this idea and provide an additional layer of evidence for the capacity of the visual system to exploit image information for shape inference. © 2017 The Authors.