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Dive into the research topics where Ayellet Tal is active.

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Featured researches published by Ayellet Tal.


IEEE Transactions on Pattern Analysis and Machine Intelligence | 2012

Context-Aware Saliency Detection

Stas Goferman; Lihi Zelnik-Manor; Ayellet Tal

We propose a new type of saliency—context-aware saliency—which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological literature. The benefits of the proposed approach are evaluated in two applications where the context of the dominant objects is just as essential as the objects themselves. In image retargeting, we demonstrate that using our saliency prevents distortions in the important regions. In summarization, we show that our saliency helps to produce compact, appealing, and informative summaries.


computer vision and pattern recognition | 2010

Context-aware saliency detection

Stas Goferman; Lihi Zelnik-Manor; Ayellet Tal

We propose a new type of saliency – context-aware saliency – which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological literature. The benefits of the proposed approach are evaluated in two applications where the context of the dominant objects is just as essential as the objects themselves. In image retargeting we demonstrate that using our saliency prevents distortions in the important regions. In summarization we show that our saliency helps to produce compact, appealing, and informative summaries.


international conference on computer graphics and interactive techniques | 2004

Modeling by example

Thomas A. Funkhouser; Michael M. Kazhdan; Philip Shilane; Patrick Min; William Kiefer; Ayellet Tal; Szymon Rusinkiewicz; David P. Dobkin

In this paper, we investigate a data-driven synthesis approach to constructing 3D geometric surface models. We provide methods with which a user can search a large database of 3D meshes to find parts of interest, cut the desired parts out of the meshes with intelligent scissoring, and composite them together in different ways to form new objects. The main benefit of this approach is that it is both easy to learn and able to produce highly detailed geometric models -- the conceptual design for new models comes from the user, while the geometric details come from examples in the database. The focus of the paper is on the main research issues motivated by the proposed approach: (1) interactive segmentation of 3D surfaces, (2) shape-based search to find 3D models with parts matching a query, and (3) composition of parts to form new models. We provide new research contributions on all three topics and incorporate them into a prototype modeling system. Experience with our prototype system indicates that it allows untrained users to create interesting and detailed 3D models.


computer vision and pattern recognition | 2013

What Makes a Patch Distinct

Ran Margolin; Ayellet Tal; Lihi Zelnik-Manor

What makes an object salient? Most previous work assert that distinctness is the dominating factor. The difference between the various algorithms is in the way they compute distinctness. Some focus on the patterns, others on the colors, and several add high-level cues and priors. We propose a simple, yet powerful, algorithm that integrates these three factors. Our key contribution is a novel and fast approach to compute pattern distinctness. We rely on the inner statistics of the patches in the image for identifying unique patterns. We provide an extensive evaluation and show that our approach outperforms all state-of-the-art methods on the five most commonly-used datasets.


The Visual Computer | 2005

Mesh segmentation using feature point and core extraction

Sagi Katz; George Leifman; Ayellet Tal

Mesh segmentation has become a necessary ingredient in many applications in computer graphics. This paper proposes a novel hierarchical mesh segmentation algorithm, which is based on new methods for prominent feature point and core extraction. The algorithm has several benefits. First, it is invariant both to the pose of the model and to different proportions between the model’s components. Second, it produces correct hierarchical segmentations of meshes, both in the coarse levels of the hierarchy and in the fine levels, where tiny segments are extracted. Finally, the boundaries between the segments go along the natural seams of the models.


ieee international conference on shape modeling and applications | 2006

Mesh Segmentation - A Comparative Study

Marco Attene; Sagi Katz; Michela Mortara; Giuseppe Patanè; Michela Spagnuolo; Ayellet Tal

Mesh segmentation has become an important component in many applications in computer graphics. In the last several years, many algorithms have been proposed in this growing area, offering a diversity of methods and various evaluation criteria. This paper provides a comparative study of some of the latest algorithms and results, along several axes. We evaluate only algorithms whose code is available to us, and thus it is not a comprehensive study. Yet, it sheds some light on the vital properties of the methods and on the challenges that future algorithms should face


Computer Graphics Forum | 2002

Metamorphosis of Polyhedral Surfaces using Decomposition

Shymon Shlafman; Ayellet Tal; Sagi Katz

This paper describes an algorithm for morphing polyhedral surfaces based on their decompositions into patches. The given surfaces need neither be genus‐zero nor two‐manifolds. We present a new algorithm for decomposing surfaces into patches. We also present a new projection scheme that handles topologically cylinder‐like polyhedral surfaces. We show how these two new techniques can be used within a general framework and result with morph sequences that maintain the distinctive features of the input models.


Computers & Graphics | 2002

Polyhedral surface decomposition with applications

Emanoil Zuckerberger; Ayellet Tal; Shymon Shlafman

Abstract This paper addresses the problem of decomposing a polyhedral surface into “meaningful” patches. We describe two decomposition algorithms—flooding convex decomposition and watershed decomposition, and show experimental results. Moreover, we discuss three applications which can highly benefit from surface decomposition. These applications include content-based retrieval of three-dimensional models, metamorphosis of three-dimensional models and simplification.


IEEE Transactions on Visualization and Computer Graphics | 2008

Online Dynamic Graph Drawing

Yaniv Frishman; Ayellet Tal

This paper presents an algorithm for drawing a sequence of graphs online. The algorithm strives to maintain the global structure of the graph and, thus, the users mental map while allowing arbitrary modifications between consecutive layouts. The algorithm works online and uses various execution culling methods in order to reduce the layout time and handle large dynamic graphs. Techniques for representing graphs on the GPU allow a speedup by a factor of up to 17 compared to the CPU implementation. The scalability of the algorithm across GPU generations is demonstrated. Applications of the algorithm to the visualization of discussion threads in Internet sites and to the visualization of social networks are provided.


Computer Graphics Forum | 1996

BOXTREE: A Hierarchical Representation for Surfaces in 3D

Gill Barequet; Bernard Chazelle; Leonidas J. Guibas; Joseph S. B. Mitchell; Ayellet Tal

We introduce the boxtree, a versatile data structure for representing triangulated or meshed surfaces in 3D. A boxtree is a hierarchical structure of nested boxes that supports efficient ray tracing and collision detection. It is simple and robust, and requires minimal space. In situations where storage is at a premium, boxtrees are effective alternatives to octrees and BSP trees. They are also more flexible and efficient than R‐trees, and nearly as simple to implement.

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Sagi Katz

Technion – Israel Institute of Technology

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George Leifman

Technion – Israel Institute of Technology

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Lihi Zelnik-Manor

Technion – Israel Institute of Technology

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Michael Kolomenkin

Technion – Israel Institute of Technology

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Gill Barequet

Technion – Israel Institute of Technology

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Gur Harary

Technion – Israel Institute of Technology

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Sigal Ar

Technion – Israel Institute of Technology

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