2185149
Monocular perception of biological motion-detection and labeling
Computer perception of biological motion is key to developing convenient and powerful human-computer interfaces. Successful body tracking algorithms have been developed; however initialization is done by hand. We propose a method for detecting a moving human body and for labeling its parts automatically. It is based on maximizing the joint probability density function (PDF) of the position and velocity of the body parts. The PDF is estimated from training data. Dynamic programming is used for calculating efficiently the best global labeling on an approximation of the PDF. The computational cost is on the order of N/sup 4/ where N is the number of features detected. We explore the performance of our method with experiments carried on a variety of periodic and non-periodic body motions viewed monocularly for a total of approximately 30,000 frames. Point-markers were strapped to the joints of the subject for facilitating image analysis. We find an average of 2.3% labeling error; the experiments also suggest a high degree of viewpoint-invariance.
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.
6822921
Unsupervised Learning of Human Motion
An unsupervised learning algorithm that can obtain a probabilistic model of an object composed of a collection of parts (a moving human body in our examples) automatically from unlabeled training data is presented. The training data include both useful "foreground" features as well as features that arise from irrelevant background clutter - the correspondence between parts and detected features is unknown. The joint probability density function of the parts is represented by a mixture of decomposable triangulated graphs which allow for fast detection. To learn the model structure as well as model parameters, an EM-like algorithm is developed where the labeling of the data (part assignments) is treated as hidden variables. The unsupervised learning technique is not limited to decomposable triangulated graphs. The efficiency and effectiveness of our algorithm is demonstrated by applying it to generate models of human motion automatically from unlabeled image sequences, and testing the learned models on a variety of sequences.
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.
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.
23745644
Parsimonious Reconstruction of Sequence Evolution and Haplotype Blocks
Under the infinite-sites model of mutation, we consider the problem of finding the minimum number of recombination events which must have occurred in the evolutionary history of sampled DNA sequences. Our approach is deterministic and is based on the combinatorics of leaf-labelled rooted trees. In contrast to previously known approaches, which only yield estimated lower bounds, our approach always gives the exact minimum number of recombination events. Furthermore, our method can be used to reconstruct explicitly evolutionary histories with the minimum number of recombination events. As an additional application, we discuss how our work can be used to define haplotype blocks.
2088404
A dispatching mechanism providing REMPLI applications with QoS
For supporting applications with different timing constraints, a PLC (power line communication) system must provide differentiated QoS (quality of service). In this paper a traffic dispatching policy is specified and implemented which guarantees both required periodic data update and short end-to-end delay of aperiodic data request services. This policy is compared with the classic dual-priority one showing its good performance
10098796
Constructing Minimal Ancestral Recombination Graphs
By viewing the ancestral recombination graph as defining a sequence of trees, we show how possible evolutionary histories consistent with given data can be constructed using the minimum number of recombination events. In contrast to previously known methods, which yield only estimated lower bounds, our method of detecting recombination always gives the minimum number of recombination events if the right kind of rooted trees are used in our algorithm. A new lower bound can be defined if rooted trees with fewer constraints are used. As well as studying how often it actually is equal to the minimum, we test how this new lower bound performs in comparison to some other lower bounds. Our study indicates that the new lower bound is an improvement on earlier bounds. Also, using simulated data, we investigate how well our method can recover the actual site-specific evolutionary relationships. In the presence of recombination, using a single tree to describe the evolution of the entire locus clearly leads to lower average recovery percentages than does our method. Our study shows that recovering the actual local tree topologies can be done more accurately than estimating the actual number of recombination events.
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.