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首页> 外文期刊>Journal of vision >Probabilistic Interpretation of Depth in Line Drawings due to T-junctions
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Probabilistic Interpretation of Depth in Line Drawings due to T-junctions

机译:T形结在线图中深度的概率解释

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Line drawings can effectively convey the 3D shape of objects despite the absence of most conventional depth cues. The 3D percept can be especially clear when drawings include internal contours and T-junctions as well as outer bounding contours. Early work that focused on cataloguing and analyzing various junction types (Huffman, 1971; Clowes, 1971; Waltz, 1972; Mackworth, 1973; Charkravarty, 1979; Malik, 1987) was limited by a dependence on deterministic junction interpretation rules. We revisit the study of T-junctions and related contour cues to depth, but now in a probabilistic framework. We hypothesized that the interpretation of surface shape in line drawings including T-junctions involves a process of probabilistic estimation of depth, based on both local and non-local cues. This formulation incorporates default (traditional) depth interpretations of junctions into a likelihood function, and can thus accommodate non-default (non-traditional) interpretations with other constraints when they are required to maximize the posterior. Moreover, the probabilistic framework allows us to quantitatively model the contribution of local and non-local depth cues, including the "propagation" of the influence of a T-junction at points various distances from it. We measured depth order for pairs of points (Koenderink et al., 1996; Koenderink et al., 2011) inside line drawings constructed so as to modulate the presence and location of critical depth cues. Observers reported the depth order of the dots, with the responses indicating the apparent 3D surface structure of the inferred shape. We found systematic effects of the location of dots with respect to the T-junctions, with systematic changes in the way depth order was interpreted as a result of the local and global structure of the contours. The findings shed light on how the local depth information drawn from T-junctions propagates and interacts with cues derived from other contours to yield a percept of the 3D surface.
机译:线条画可以有效地传达对象的3D形状,尽管没有大多数常规的深度提示。当工程图包含内部轮廓和T形结以及外部边界轮廓时,3D感知可能会特别清晰。早期的工作着重于对各种路口类型进行分类和分析(霍夫曼(Huffman),1971年;霍夫斯(Clowes),1971年;沃尔兹(Waltz),1972年;麦可沃思(Mackworth),1973年;查克拉瓦蒂(Charkravarty),1979年;马利克(Malik),1987年)受到对确定性路口解释规则的依赖。我们重新研究了T形结和相关轮廓提示的深度,但是现在处于概率框架中。我们假设线形图(包括T型结)中表面形状的解释涉及基于本地和非本地提示的深度概率估计过程。此公式将交界处的默认(传统)深度解释合并到似然函数中,因此当需要最大化后验时,可以使用具有其他约束的非默认(非传统)解释。而且,概率框架使我们能够定量地模拟局部和非局部深度线索的贡献,包括在距T结不同距离的点处“传播”影响的“传播”。我们在绘制的线图中测量了成对点的深度顺序(Koenderink等,1996; Koenderink等,2011),以调节关键深度提示的存在和位置。观察者报告了点的深度顺序,响应表明所推断形状的明显3D表面结构。我们发现点相对于T形结的位置的系统影响,以及由于轮廓的局部和全局结构而导致的深度顺序解释方式的系统变化。这些发现揭示了从T形接合处提取的局部深度信息如何传播并与其他轮廓产生的线索相互作用,以产生3D表面的感知。

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