26613232
Learning Actions Using Robust String Kernels
This paper presents an action analysis method based on robust string matching using dynamic programming. Similar to matching text sequences, atomic actions based on semantic and structural features are first detected and coded as spatio-temporal characters or symbols. These symbols are subsequently concatenated to form a unique set of strings for each action. A similarity metric using longest common subsequence algorithm is employed to robustly match action strings with variable length. A dynamic programming method with polynomial computational complexity and linear space complexity is implemented. An effective learning scheme based on similarity metric embedding is developed to deal with matching strings of variable length. Our proposed method works with limited amount of training data and exhibits desirable generalization property. Moreover, it can be naturally extended to detect compound behaviors and events. Experimental evaluation on our own and a commonly used data set demonstrates that our method allows for large pose and appearance changes, is robust to background clutter, and can accommodate spatio-temporal behavior variations amongst different subjects while achieving high discriminability between different behaviors.
13996299
Action video retrieval based on atomic action vocabulary
We propose an efficient action retrieval system that is based on a novel action representation and an effective video matching method. We represent actions with a hierarchical encoding scheme that at low-level measures local body parts motions, which then evolves into encoding of instantaneous global body motions and finally high-level description of actions through atomic action vocabulary. Atomic action vocabulary extends the notion of keyframe-based indexing techniques, where a long action video is decomposed into a sequence of atomic sub-actions matched from the vocabulary. Efficient video matching is achieved by exploiting precomputed inter-vocabulary distances so that global video distance between video sequences can be computed in a very efficient manner that is equivalent to index lookup operations with minimal additional computational loads. Combined with atomic action vocabulary, this can provide flexible video matching schemes of finding compound action sequences of arbitrary lengths. The proposed approach is evaluated on surveillance video and a public video dataset.
9659860
True multi-image alignment and its application to mosaicing and lens distortion correction
Multiple images of a scene are related through 2D/3D view transformations and linear and non-linear camera transformations. In all the traditional techniques to compute these transformations, especially the ones relying on direct intensity gradients, one image and its coordinate system have been assumed to be ideal and distortion free. In this paper, we present a formulation and an algorithm for true multi-image alignment that does not rely on the measurements of a reference image being distortion free. For instance, in the presence of lens distortion, none of the images can be assumed to be ideal. In our formulation, all the images are modeled as intensity measurements represented in their respective coordinate systems, each of which is related to an ideal coordinate system through an interior camera transformation and an exterior view transformation. The goal of the accompanying algorithm is to compute an image in the ideal coordinate system while solving for the transformations that relate the ideal system with each of the data images. Key advantages of the technique presented in this paper are: (i) no reliance on one distortion free image, (ii) ability to register images and compute coordinate transformations even when the multiple images are of an extended scene with no overlap between the first and last frame of the sequence, and (iii) ability to handle linear and non-linear transformations within the same framework. The new algorithm is evaluated in the context of two applications: (i) correction of lens distortion, and (ii) creation of video mosaics.
6283962
Multi-view 3D analysis with applications for augmented reality and enhanced video visualization
The article presents methods for 3D scene geometry recovery/refinement and pose estimation from motion imagery in two representative scenarios. First, we present a method for pose estimation and scene geometry recovery from extended sequences without prior knowledge of the scheme. Second, we discuss how to recover camera poses when a rough scene model is provided. We show how to extend and refine the scene model using the recovered poses. Finally, we present applications of the above techniques for 3D imagery manipulation such as enhanced visualization for video and 3D insertion of synthetic objects in the imagery.
5884426
Validation of an optical flow method for tag displacement estimation
Presents a validation study of an optical-flow method for the rapid estimation of myocardial displacement in magnetic resonance tagged cardiac images. This registration and change visualization (RCV) software uses a hierarchical estimation technique to compute the flow field that describes the warping of an image of one cardiac phase into alignment with the next. This method overcomes the requirement of constant pixel intensity in standard optical-flow methods by preprocessing the input images to reduce any intensity bias which results from the reduction in stripe contrast throughout the cardiac cycle. To validate the method, SPAMM-tagged images were acquired of a silicon gel phantom with simulated rotational motion. The pixel displacement was estimated with the RCV method and the error in pixel tracking was <4% 1000 ms after application of the tags, and after 30/spl deg/ of rotation. An additional study was performed using a SPAMM-tagged multiphase slice of a canine left ventricle. The true displacement was determined using a previously validated active contour model (snakes). The error between methods was 6.7% at end systole. The RCV method has the advantage of tracking all pixels in the image in a substantially shorter period than the snakes method.
31836660
A Global Matching Framework for Stereo Computation
This paper presents a new global matching framework f o r stereo computation. In this framework, the second view is first predicted front the reference view using the depth information. A global match measure is then defined as the similarity function between the predicted image and the actual image. Stereo coniputcction is converted into a search problem where the goal is to find the depth rnup that maximizes the global match measure. The major advantage of this framework is that the global visibility constraint is inherently enforced in the computation. This paper explores several key components of this framework including ( I ) three color segmentation based depth representations, (2) an incremental warping algorithm that dramatically reduces the computational complexity, and (3) scene constraints such as the smoothness constraint and the color sinzilarity constraint. Experimental results using different types of depth representations are presented. The quality of the computed depth maps is demonstrated through image-based rendering from new viewpoints.
10455339
Pollution in P2P file sharing systems
One way to combat P2P file sharing of copyrighted content is to deposit into the file sharing systems large volumes of polluted files. Without taking sides in the file sharing debate, in this paper we undertake a measurement study of the nature and magnitude of pollution in the FastTrack P2P network, currently the most popular P2P file sharing system. We develop a crawling platform which crawls the majority of the FastTrack Network's 20,000+ supernodes in less than 60 minutes. From the raw data gathered by the crawler for popular audio content, we obtain statistics on the number of unique versions and copies available in a 24-hour period. We develop an automated procedure to detect whether a given version is polluted or not, and we show that the probabilities of false positives and negatives of the detection procedure are very small. We use the data from the crawler and our pollution detection algorithm to determine the fraction of versions and fraction of copies that are polluted for several recent and old songs. We observe that pollution is pervasive for recent popular songs. We also identify and describe a number of anti-pollution mechanisms.
113025
Distributed peak power management for many-core architectures
Recently proposed techniques for peak power management involve centralized decision-making and assume quick evaluation of the various power management states. These techniques do not prevent instantaneous power from exceeding the peak power budget, but instead trigger corrective action when the budget has been exceeded. Similarly, they are not suitable for many-core architectures (processors with tens or possibly hundreds of cores on the same die) due to an exponential explosion in the number of global power management states. In this paper, we look at a hierarchical and a gradient ascent-based technique for decentralized peak power management for many-core architectures. The proposed techniques prevent power from exceeding the peak power budget and enable the placement of several more cores on a die than what the power budget would normally allow. We show up to 47% (33% on average) improvements in throughput for a given power budget. Our techniques outperform the static oracle by 22%.
135903312
Determination of the hardness and elastic modulus of low- k thin films and their barrier layer for microelectronic applications
This paper presents the experimental results and analysis of the elastic modulus and hardness for several thicknesses of dielectric films, namely low-k films and their barrier layer, using the nano-indentation technique. The elastic modulus and hardness of the films were determined by "normal" nano-indentation analysis. The data were then analyzed by rearranging the load-displacement data (P-h) obtained by nano-indentation in such a way that the applied load divided by the corresponding displacement (P/h) versus the displacement (h) was obtained, which effectively differentiates the film-only mechanical properties from those of the substrate. The low-k film, carbon-doped silicon oxide (SiOC), was prepared using a parallel plate PECVD system. The dielectric constant of the low-k film was measured to be 3.09, which is much lower than that of commonly used dielectric materials such as SiO2 (k ∼ 3.9). The hardness and elastic modulus of the film were measured to be approximately 2.23 and 13.98 GPa, respectively. To enhance the mechanical properties of the low-k thin film, a low-k barrier layer (SiCN:H) with better mechanical properties was deposited between the low-k film and the substrate or on top of the low-k film. It was found that the barrier layer improved the mechanical properties of the low-k film and the barrier layer stacked in certain circumstances. The effects of the arrangement of the barrier layer and the low-k film on the mechanical behavior of the bi-layer system were studied in detail.
16117863
A Comparative Study of Different Sensors for Smart Car Park Management
Wireless sensor networks offer a very attractive, low cost alternative for traffic monitoring and surveillance in car parking, freeways and intersection in different environmental conditions. In such systems, robust and reliable vehicle detection is a critical step, thus it is important to carefully evaluate the different modes of operations in order to address existing issues. This paper proposes a vision of improvements to wireless sensor car parking network system by presenting valuable comparison data for different sensors using different type of software functions and hardware components. The main goal of this work is to present a simple, automated analysis and comparison of power management, communication efficiency and threshold times using different sensors and a corresponding prediction of the above features. The results show a clear difference in various parameters by using different types of sensors for vehicle detection.
7664388
Processor Power Reduction Via Single-ISA Heterogeneous Multi-Core Architectures
This paper proposes a single-ISA heterogeneousmulti-core architecture as a mechanism to reduce processorpower dissipation. It assumes a single chip containing a diverseset of cores that target different performance levels and consumedifferent levels of power. During an application’s execution,system software dynamically chooses the most appropriate core tomeet specific performance and power requirements. It describesan example architecture with five cores of varying performanceand complexity. Initial results demonstrate a five-fold reductionin energy at a cost of only 25% performance.