Recovering Structure fromr-Sampled Objects
نویسندگان
چکیده
منابع مشابه
Recovering Structure from r-Sampled Objects
For a surface F in 3-space that is represented by a set S of sample points, we construct a coarse approximating polytope P that uses a subset of S as its vertices and preserves the topology ofF . In contrast to surface reconstruction we do not use all the sample points, but we try to use as few points as possible. Such a polytope P is useful as a ‘seed polytope’ for starting an incremental refi...
متن کاملRecovering the Precise Heart Rate from Sparsely Sampled Electrocardiograms
This work deals with a potential possibilities of improvement to the precision of time dependencies (e. g. heart rate) derived from a standard digital Holter record. The sampling frequency of a typical 24-hour ECG record is usually a compromise between signal quality and memory requirements. But even with a sampling interval of about 8 ms, is still possible to maintain the accuracy of 1...2 ms ...
متن کاملRecovering Shared Objects Without Stable Storage
This paper considers the problem of building fault-tolerant shared objects when processes can crash and recover but lose their persistent state on recovery. This Diskless Crash-Recovery (DCR) model matches the way many long-lived systems are built. We show that it presents new challenges, as operations that are recorded at a quorum may not persist after some of the processes in that quorum cras...
متن کاملInteractive 3D Painting on Point-Sampled Objects
We present a novel painting system for 3D objects. In order to overcome parameterization problems of existing applications, we propose a unified sample-based approach to represent geometry and appearance of the 3D object as well as the brush surface. The generalization of 2D pixel-based paint models to point samples allows us to elegantly simulate paint transfer for 3D objects. In contrast to m...
متن کاملMultiple visual objects are sampled sequentially
When acting in a complex visual environment, it is essential to be able to flexibly allocate attention to parts of the visual scene that may contain goal-relevant information. The paper by Jia et al. provides novel evidence that our brains sequentially sample different objects in a visual scene. The results were obtained using "temporal response functions," in which unique electroencephalograph...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Graphics Forum
سال: 2009
ISSN: 0167-7055,1467-8659
DOI: 10.1111/j.1467-8659.2009.01512.x