Results 1 - 10 of 494

Entropy rate superpixel segmentation

by Ming-yu Liu, Oncel Tuzel, Srikumar Ramalingam , 2011
"... We propose a new objective function for superpixel segmentation. This objective function consists of two components: entropy rate of a random walk on a graph and a balancing term. The entropy rate favors formation of compact and homogeneous clusters, while the balancing function encourages clusters ..."
Abstract - Cited by 33 (1 self) - Add to MetaCart
under the matroid constraint. By exploiting submodular and monotonic properties of the objective function, we develop an efficient greedy algorithm. Furthermore, we prove an approximation bound of 1 2 for the optimality of the solution. Extensive experiments on the Berkeley segmentation benchmark show

Rodinia: A Benchmark Suite for Heterogeneous Computing

by Shuai Che, Michael Boyer, Jiayuan Meng, David Tarjan, Jeremy W. Sheaffer, Sang-ha Lee, Kevin Skadron , 2009
"... This paper presents and characterizes Rodinia, a benchmark suite for heterogeneous computing. To help architects study emerging platforms such as GPUs (Graphics Processing Units), Rodinia includes applications and kernels which target multi-core CPU and GPU platforms. The choice of applications is ..."
Abstract - Cited by 200 (17 self) - Add to MetaCart
is inspired by Berkeley’s dwarf taxonomy. Our characterization shows that the Rodinia benchmarks cover a wide range of parallel communication patterns, synchronization techniques and power consumption, and has led to some important architectural insight, such as the growing importance of memory

Benchmarking Image Segmentation Algorithms

by Francisco J. Estrada, et al. , 2009
"... We present a thorough quantitative evaluation of four image segmentation algorithms on images from the Berkeley Segmentation Database. The algorithms are evaluated using an efficient algorithm for computing precision and recall with regard to human ground-truth boundaries. We test each segmentation ..."
Abstract - Cited by 15 (0 self) - Add to MetaCart
We present a thorough quantitative evaluation of four image segmentation algorithms on images from the Berkeley Segmentation Database. The algorithms are evaluated using an efficient algorithm for computing precision and recall with regard to human ground-truth boundaries. We test each

Toward Objective Evaluation of Image Segmentation Algorithms

by Ranjith Unnikrishnan, Caroline Pantofaru, Martial Hebert , 2007
"... Unsupervised image segmentation is an important component in many image understanding algorithms and practical vision systems. However, evaluation of segmentation algorithms thus far has been largely subjective, leaving a system designer to judge the effectiveness of a technique based only on intui ..."
Abstract - Cited by 141 (3 self) - Add to MetaCart
measure of similarity, the Normalized Probabilistic Rand (NPR) index, can be used to perform a quantitative comparison between image segmentation algorithms using a hand-labeled set of ground-truth segmentations. We show that the measure allows principled comparisons between segmentations created

Reducing power in superscalar processor caches using subbanking, multiple line buffers and bit-line segmentation

by Kanad Ghose, Milind B. Kamble - In International Symposium on Low Power Electronics and Design , 1999
"... Modern microprocessors employ one or two levels of on–chip caches to bridge the burgeoning speed disparities between the processor and the RAM. These SRAM caches are a major source of power dissipation. We investigate architectural techniques, that do not compromise the processor cycle time, for red ..."
Abstract - Cited by 135 (3 self) - Add to MetaCart
, optimized for a 300 MHz. clock. We show that a combination of subbanking, multiple line buffers and bit–line segmentation can reduce the on–chip cache power dissipation by as much as 75 % in a technology–independent manner. Key words: Low power caches, power estimation. 1.

Performance Evaluation and Benchmarking of Six Page Segmentation Algorithms

by Faisal Shafait, Daniel Keysers, Thomas M. Breuel , 2007
"... Informative benchmarks are crucial for optimizing the page segmentation step of an OCR system, frequently the performance limiting step for overall OCR system performance. We show that current evaluation scores are insufficient for diagnosing specific errors in page segmentation and fail to identify ..."
Abstract - Cited by 30 (20 self) - Add to MetaCart
Informative benchmarks are crucial for optimizing the page segmentation step of an OCR system, frequently the performance limiting step for overall OCR system performance. We show that current evaluation scores are insufficient for diagnosing specific errors in page segmentation and fail

Key-segments for video object segmentation

by Yong Jae Lee, Jaechul Kim, Kristen Grauman - In ICCV , 2011
"... We present an approach to discover and segment foreground object(s) in video. Given an unannotated video sequence, the method first identifies object-like regions in any frame according to both static and dynamic cues. We then compute a series of binary partitions among those candidate “key-segments ..."
Abstract - Cited by 60 (3 self) - Add to MetaCart
oversegmentation. We apply our method to challenging benchmark videos, and show competitive or better results than the state-of-the-art. 1.

Waterfall Segmentation of Complex Scenes

by Allan Hanbury, Beatriz Marcotegui - Lecture Notes in Computer Science 3851 , 2006
"... Abstract. We present an image segmentation technique using the mor-phological Waterfall algorithm. Improvements in the segmentation are brought about by using improved gradients. These are based on the detection of object boundaries learnt from human segmentations intro-duced by Martin et al. (2004) ..."
Abstract - Cited by 6 (2 self) - Add to MetaCart
for numerical images recently introduced by Beucher (2005). Resulting segmentations are com-pared to human segmentations using the Berkeley segmentation bench-mark. The benchmark results show that the proposed segmentation al-gorithm produces segmentations comparable to those produced by the Normalised Cuts

Salient Object Detection: A Benchmark

by Ali Borji, Dicky N. Sihite, Laurent Itti
"... Abstract. Several salient object detection approaches have been published which have been assessed using different evaluation scores and datasets resulting in discrepancy in model comparison. This calls for a methodological framework to compare existing models and evaluate their pros and cons. We an ..."
Abstract - Cited by 51 (2 self) - Add to MetaCart
on segmentation datasets compared to salient object detection algorithms. Further, we propose combined models which show that integration of the few best models outperforms all models over other datasets. By analyzing the consistency among the best models and among humans for each scene, we identify the scenes

File System Logging Versus Clustering: A Performance Comparison

by Margo Seltzer, Keith A. Smith, Hari Balakrishnan, Jacqueline Chang, Sara Mcmains, Venkata Padmanabhan , 1995
"... The Log-structured File System (LFS), introduced in 1991 [8], has received much attention for its potential order-of-magnitude improvement in file system performance. Early research results [9] showed that small file performance could scale with processor speed and that cleaning costs could be kept ..."
Abstract - Cited by 124 (11 self) - Add to MetaCart
by as much as 40% [10]. The same work showed that the addition of clustered reads and writes in the Berkeley Fast File System [6] (FFS) made it competitive with LFS in large-file handling and software development environments as approximated by the Andrew benchmark [4]. These seemingly inconsistent results
Results 1 - 10 of 494