9240638
An Irregular Search Window Reuse Scheme for Motion Estimation in MPEG-2 to H.264 Transcoding
Motion estimation (ME) is a computation-intensive operation in video coding system. In MPEG-2 to H.264 transcoding, motion vector (MV) from MPEG-2 reused as search center in H.264 encoder is a simple but effective technique to simplify ME procedure. However directly introducing MPEG-2 MV will bring irregular overlapping between search windows of successive macroblocks (MB) which invalidates the data reuse scheme in hardware design of ME module. In this paper, the authors propose a search window reuse scheme for transcoding in HDTV application. By utilizing the similarity between neighboring MVs, overlapping of search windows between successive MBs can be regularized. Experiment results show that our method achieve average 93.1% search window reuse rate in HDTV sequence with almost no video quality degradation. And the bandwidth can be reduced to 92.5 Mbytes/s based on theoretical calculation which is only 40.6% of that without this scheme.
7056002
A VLSI array processing oriented fast fourier transform algorithm and hardware implementation
Many parallel Fast Fourier Transform (FFT) algorithms adopt multiple stages architecture to increase performance. However, data permutation between stages consumes volume memory and processing time. An FFT array processing mapping algorithm is proposed in this paper to overcome this demerit. In this algorithm, arbitrary 2k butterfly units (BUs) could be scheduled to work in parallel on n=22 data (k=0, 1,..., s-1). Because no inter stage data transfer is required, memory consumption is reduced to 1/3 of the original algorithm. Moreover, with the increasing of BUs, not only does throughput increase linearly, system latency also decreases linearly. This array processing orientated architecture provides flexible tradeoff between hardware cost and system performance. An 18-bit word-length 1024-point FFT architecture with 4 BUs is given to demonstrate this mapping algorithm. The design is implemented with TSMC 0.18μm CMOS technology. The core area is 2.99x1.12mm 2 and clock frequency is 326MHz in typical condition (1.8V, 25°C). This processor could complete 1024 FFT calculation in 7.839μs.
7172331
Enhanced Strict Multilevel Successive Elimination Algorithm for Fast Motion Estimation
This paper presents an enhanced strict multilevel successive elimination algorithm (EMSEA) for fast block-matching motion estimation, which is based on the previous strict multilevel successive elimination algorithm (SMSEA) (Song et al., 2006). Different to the SMSEA algorithm with fixed parameters, in EMSEA algorithm, the whole search area is divided into two regions and each region has its own parameters. Therefore, the computation complexity of SMSEA algorithm can be further decreased. Experiments show that the proposed EMSEA algorithm can reduce 16.2% of the SMSEA computation and maintain almost the same image quality, which is better than the TSS and DS algorithms.
16829828
Algorithms for Imperfect Phylogeny Haplotyping (IPPH) with a Single Homoplasy or Recombination Event
The haplotype inference (HI) problem is the problem of inferring 2n haplotype pairs from n observed genotype vectors. This is a key problem that arises in studying genetic variation in populations, for example in the ongoing HapMap project [5]. In order to have a hope of finding the haplotypes that actually generated the observed genotypes, we must use some (implicit or explicit) genetic model of the evolution of the underlying haplotypes. The Perfect Phylogeny Haplotyping (PPH) model was introduced in 2002 [9] to reflect the “neutral coalescent” or “perfect phylogeny” model of haplotype evolution. The PPH problem (which can be solved in polynomial time) is to determine whether there is an HI solution where the inferred haplotypes can be derived on a perfect phylogeny (tree). 
 
Since the introduction of the PPH model, several extensions and modifications of the PPH model have been examined. The most important modification, to model biological reality better, is to allow a limited number of biological events that violate the perfect phylogeny model. This was accomplished implicitly in [7,12] with the inclusion of several heuristics into an algorithm for the PPH problem [8]. Those heuristics are invoked when the genotype data cannot be explained with haplotypes that fit the perfect phylogeny model. In this paper, we address the issue explicitly, by allowing one recombination or homoplasy event in the model of haplotype evolution. We formalize the problems and provide a polynomial time solution for one problem, using an additional, empirically-supported assumption. We present a related framework for the second problem which gives a practical algorithm. We believe the second problem can be solved in polynomial time.
28755708
Automatically generating metadata for digital photographs with geographic coordinates
Given location information on digital photographs, we can automatically generate an abundance of photo-related metadata using off-the-shelf and web-based data sources. These metadata can serve as additional memory cues and filters when browsing a personal or global collection of photos.
1562361
Learning probabilistic structure for human motion detection
Decomposable triangulated graphs have been shown to be efficient and effective for modeling the probabilistic spatio-temporal structure of brief stretches of human motion. In previous work such model structure was handcrafted by expert human observers and labeled data were needed for parameter learning. We present a method to build automatically the structure of the decomposable triangulated graph from unlabeled data. It is based on maximum-likelihood. Taking the labeling of the data as hidden variables, a variant of the EM algorithm can be applied. A greedy algorithm is developed to search for the optimal structure of the decomposable model based on the (conditional) differential entropy of variables. Our algorithm is demonstrated by learning models of human motion completely automatically from unlabeled real image sequences with clutter and occlusion. Experiments on both motion captured data and grayscale image sequences show that the resulting models perform better than the hand-constructed models.
1116497
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatically from unlabeled data. The distinguished part of this work is that it is based on unlabeled data, i.e., the training features include both useful foreground parts and background clutter and the correspondence between the parts and detected features are unknown. We use decomposable triangulated graphs to depict the probabilistic independence of parts, but the unsupervised technique is not limited to this type of graph. In the new approach, labeling of the data (part assignments) is taken as hidden variables and the EM algorithm is applied. A greedy algorithm is developed to select parts and to search for the optimal structure based on the differential entropy of these variables. The success of our algorithm is demonstrated by applying it to generate models of human motion automatically from unlabeled real image sequences.
7144496
Loss-tolerant QoS using firm constraints in guaranteed rate networks
We propose a trade-off between hard and soft real-time guarantees to maintain an acceptable QoS guarantee in overload condition and maximize efficiently the utilization of network resources. The key of our solution is that many real-time applications are loss-tolerant, but the loss profile must be well defined since successive packet losses are not suitable. We use the concept of (m,k)-firm timing constraints to define a novel guaranteed loss-tolerant QoS. Therefore, we extend the basic WFQ algorithm to take into account the firm timing constraints to provide lower delay guarantees without violating bandwidth fairness or misusing network resources. The proposal is called (m,k)-WFQ. Using network calculus formalism, analytic study gives the deterministic delay bound provided by the (m,k)-WFQ algorithm for upper bounded arrival curve traffic. Theoretical results and simulations show a noticeable improvement on delay guarantee made by (m,k)-WFQ compared to standard WFQ algorithm without much degrading bandwidth fairness.