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Communications of the ACM

121 - 130 of 2,393 for bentley

Streaming matching of events

Streaming matching of events based on its content has many applications including customer subscriptions or recommendations for new ads. Customer subscriptions system requires minimal delay between event appearance and corresponding notifications. Such system should be horizontally scalable with regard to events and customers. There are many approaches to solving this task ranging from brute-force ones to utilizing some complex data structures. We present our approach integrated into several high-loaded production services at Yandex.Classifieds.

Audio-based head motion synthesis for Avatar-based telepresence systems

In this paper, a data-driven audio-based head motion synthesis technique is presented for avatar-based telepresence systems. First, head motion of a human subject speaking a custom corpus is captured, and the accompanying audio features are extracted. Based on the aligned pairs between audio features and head motion (audio-headmotion), a K-Nearest Neighbors (KNN) based dynamic programming algorithm is used to synthesize novel head motion given new audio input. This approach also provides optional intuitive keyframe (key head poses) control: after key head poses are specified, this method will synthesize appropriate head motion sequences that maximally meet the requirements of both the speech and key head poses.

Feature match: an efficient low dimensional PatchMatch technique

Computing the dense Approximate Nearest-Neighbour Field (ANNF) between a pair of images has become a major problem which is being tackled by the image processing community in the recent years. Two important papers viz. PatchMatch [3] and CSH [11] have been developed over the past few years based on the coherency between images, but one major problem both these papers have is that image patches are treated as high dimensional vector features. In this paper we present a novel idea to reduce the dimensions of a p-by-p patch of color image to a set of low level features. This reduced dimension feature vector is used to compute the ANNF. Using these features we show that instead of dealing with image patches as p2 dimensional vectors, dealing with them in a lower dimension gives a much better approximation for the nearest-neighbour field as compared to the state of the art. We further present a modification which improves the ANNF to give more accurate color information and show that using our improved algorithm we do not need a pair of related images to compute the ANNF like in other algorithms, i.e. we can generate the ANNF for all the images using unrelated image pairs or even from a universal source image.

Shape grammars and grammatical evolution for evolutionary design

We describe the first steps in the adoption of Shape Grammars with Grammatical Evolution for application in Evolutionary Design. Combining the concepts of Shape Grammars and Genetic Programming opens up the exciting possibility of truly generative design assist tools. In this initial study we provide some background on the adoption of grammar-based Genetic Programming for Evolutionary Design, describe Shape Grammars, and give a brief overview of Grammatical Evolution before detailing how Grammatical Evolution used Shape Grammars to successfully rediscover some benchmark target structures.

Efficient traffic crash and snow complaint GIS system

We describe the design and implementation of a traffic crash and snow complaint GIS system developed for the Lincoln Public Works department. We also describe a novel geocoding algorithm that was used to move data from the older Criminal Justice Information System, which is a relational database, to the new GIS system. In addition, we describe the implementation of several indexing algorithms that enable the system to efficiently answer rectangular range queries and queries about the relative locations of moving objects.

Computing technologies for reflective, creative care of people with dementia

Mobile apps manage data on individual residents to help carers deliver more person-centered care.

Fast nearest neighbor retrieval for bregman divergences

We present a data structure enabling efficient nearest neighbor (NN) retrieval for bregman divergences. The family of bregman divergences includes many popular dissimilarity measures including KL-divergence (relative entropy), Mahalanobis distance, and Itakura-Saito divergence. These divergences present a challenge for efficient NN retrieval because they are not, in general, metrics, for which most NN data structures are designed. The data structure introduced in this work shares the same basic structure as the popular metric ball tree, but employs convexity properties of bregman divergences in place of the triangle inequality. Experiments demonstrate speedups over brute-force search of up to several orders of magnitude.

From silhouettes to 3D points to mesh: towards free viewpoint video

This paper presents a system for 3D reconstruction from video sequences acquired in multi-camera environments. In particular, the 3D surfaces of foreground objects in the scene are extracted and represented by polygon meshes. Three stages are concatenated to process multi-view data. First, a foreground segmentation method extracts silhouettes of objects of interest. Then, a 3D reconstruction strategy obtains a cloud of oriented points that lie on the surfaces of the objects of interest in a spatially bounded volume. Finally, a fast meshing algorithm provides a topologically correct interpolation of the surface points that can be used for both visualization and further mesh processing purposes. The quality of the results (computational load) obtained by our system compares favorably against a baseline system built from state-of-the-art techniques for similar processing times (quality of the results).

The P-tree algebra

The Peano Count Tree (P-tree) is a quadrant-based lossless tree representation of the original spatial data. The idea of P-tree is to recursively divide the entire spatial data, such as Remotely Sensed Imagery data, into quadrants and record the count of 1-bits for each quadrant, thus forming a quadrant count tree. Using P-tree structure, all the count information can be calculated quickly. This facilitates efficient ways for data mining. In this paper, we will focus on the algebra and properties of P-tree structure and its variations. We have implemented fast algorithms for P-tree generation and P-tree operations. Our performance analysis shows P-tree has small space and time costs compared to the original data. We have also implemented some data mining algorithms using P-trees, such as Association Rule Mining, Decision Tree Classification and K-Clustering.

Practice-based CSCW Research: ECSCW bridging across the Atlantic

Practice-based CSCW research is an orientation towards empirically-grounded research embracing particular methodological approaches with the aim of creating new theory about work, collaboration, and cooperative technologies. While practice-based CSCW research has several strong roots in both North America and Europe: ECSCW and Europe remain central to this tradition. In this panel we will discuss the practice-based research approach asking questions such as: What is the nature of Practice-based Computer Supported Cooperative Work research? How is it different from other CSCW research approaches? What is the relationship between these traditions in terms of conceptual approaches, methodologies and open questions for future research? This panel will discuss openly the diversity and commonalities between different CSCW traditions - and argue that practice-based CSCW research is not something that happens only at ECSCW. ECSCW is not a geographical boundary for a certain type of research - but rather a place for a specific research tradition and approach with links to many academic places in the world.