1068580
Visual contour tracking based on particle filters
Abstract The Condensation algorithm, developed for visual tracking, is a variant of particle filter. In the sampling stage of Condensation, no use is made of the information from the current frame in the image sequence. As a consequence, the algorithm requires a large number of particles and is computationally expensive. In this paper, a Kalman particle filter (KPF) and an unscented particle filter (UPF) are applied to contour tracking to try to overcome the problem. These algorithms use the Kalman filter or unscented Kalman filter to incorporate information from the current frame. This sampling strategy can effectively steer the set of particles towards regions with high likelihood, and therefore can considerably reduce the number of particles needed for tracking. Performance comparisons show that the KPF is an improvement over Condensation, while the UPF has a much higher computational cost for equal tracking error.
42009299
Probabilistic Object Tracking Based on Machine Learning and Importance Sampling
The paper presents a novel particle filtering framework for visual object tracking. One of the contributions is the development of a likelihood function based on one of machine learning algorithm–AdaBoost algorithm. The likelihood function can capture the structure characteristics of one class of objects, and is thus robust to clutters and noise in the complex background. The other contribution is the adoption of mean shift iteration as a proposal distribution, which can steer discrete samples towards regions which most likely contain the targets, and is therefore leading to computational efficiency in the algorithm. The effectiveness of such a framework is demonstrated with a particular class of objects–human faces.
18829609
Proposal of Novel Histogram Features for Face Detection
This paper presents novel features for face detection in the paradigm of AdaBoost algorithm. Features are multi-dimensional histograms computed from a set of rectangles in the filtered images, and they represent marginal distributions of these rectangles. The filter banks consist of intensity, Laplacian of Gaussian (Difference of Gaussians), and Gabor filters, aiming at capturing spatial and frequency properties of human faces at different scales and different orientations. The best features selected by AdaBoost, pairs of filter and rectangle, can thus be interpreted as boosted marginal distributions of human faces. The result of preliminary experiments demonstrate that the selected features are much more powerful to describe the face pattern than the simple features of Viola and Jones and some variants which can only capture several moments of ONE dimensional histogram in intensity images.
12395366
Image Cues Fusion for Object Tracking Based on Particle Filter
Particle filter is a powerful algorithm to deal with non-linear and non-Gaussian tracking problems. However the algorithm relying only upon one image cue often fails in challenging scenarios. To overcome this, the paper first presents a color likelihood to capture color distribution of the object based on Bhattacharry coefficient, and a structure likelihood representing high level knowledge regarding the object. Together with the widely used edge likelihood, the paper further proposes a straightforward image cues fusion for object tracking in the framework of particle filter, under assumption that the visual measurement of each image cue is independent of each other. The experiments on real image sequences have shown that the method is effective, robust to illumination changes, pose variations and complex background.
6463215
Design and implementation of parallel video encoding strategies using divisible load analysis
The processing time needed for motion estimation usually accounts for a significant part of the overall processing time of the video encoder. To improve the video encoding speed, reducing the execution time for motion estimation process is essential. Parallel implementation of video encoding systems using either the software or the hardware approach has attracted much attention in the area of real time video coding. In this paper, we attempt to implement a video encoder on a bus network. Usually, for such a parallel system, the key concern is associated with partitioning and balancing of the computational load among the processors such that the overall processing time of the video encoder is minimized. With the use of the divisible load theory (DLT) paradigm, a strip-wise load partitioning/balancing scheme, a load distribution strategy, two implementation strategies are developed to exploit the data parallelism inherent in the video encoding process. The striking feature of our design is that,both the granularity of the load partitions and all the associated overheads caused during parallel video encoding process can be explicitly considered. This significantly contributes to the minimization of the overall processing time of the video encoder. Extensive experimental studies are carried out to test the effectiveness of the proposed strategies. The performance of the parallel video encoder is quantified using the metrics speedup and performance gain, respectively. The experimental results show that our strategies are effective for exploiting the available parallelism inherent in the video encoding process and provide a theoretical insight on how to analytically quantify and minimize the overall processing time of a parallel system. The proposed strategies can be easily extended and applied to improve other existing parallel systems.
1157010
Downgrading policies and relaxed noninterference
In traditional information-flow type systems, the security policy is often formalized as noninterference properties. However, noninterference alone is too strong to express security properties useful in practice. If we allow downgrading in such systems, it is challenging to formalize the security policy as an extensional property of the system.This paper presents a generalized framework of downgrading policies. Such policies can be specified in a simple and tractable language and can be statically enforced by mechanisms such as type systems. The security guarantee is then formalized as a concise extensional property using program equivalences. This relaxed noninterference generalizes traditional pure noninterference and precisely characterizes the information released due to downgrading.
42771841
Passive velocity field control of mechanical manipulators
Two concepts for the task specification and control for mechanical manipulators are advocated: the coding of tasks in terms of velocity fields; and controllers that maintain the passivity relationship between the manipulator and its physical environment. A passive velocity field tracking controller is proposed. The proposed dynamic controller mimics a flywheel: it stores and releases energy to the manipulator, but does not generate any. The controller has the interesting property that it stabilizes any multiple (positive or negative) of the desired velocity field, and exponentially stabilizes the particular multiple which is related to the total kinetic energy of the manipulator+controller.
1488910
Modeling interconnect variability using efficient parametric model order reduction
Assessing IC manufacturing process fluctuations and their impacts on IC interconnect performance has become unavoidable for modern DSM designs. However, the construction of parametric interconnect models is often hampered by the rapid increase in computational cost and model complexity. In this paper we present an efficient yet accurate parametric model order reduction algorithm for addressing the variability of IC interconnect performance. The efficiency of the approach lies in a novel combination of low-rank matrix approximation and multi-parameter moment matching. The complexity of the proposed parametric model order reduction is as low as that of a standard Krylov subspace method when applied to a nominal system. Under the projection-based framework, our algorithm also preserves the passivity of the resulting parametric models.
2303584
Constructing high assurance asynchronous real-time distributed systems: a proof-based system engineering approach
Asynchronous real-time distributed systems raise fundamental issues of how to build timely systems that operate in the presence of uncertain timeliness, and furthermore, how to certify that such systems will deliver properties including timeliness and safety. In this paper, we discuss an approach for constructing certifiable asynchronous real-time distributed systems.