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.
25332181
A Heterogeneous Feature-based Image Alignment Method
In this paper, we propose a robust heterogeneous feature based image alignment method that utilizes points, lines and regions in a unified framework. The image motion is decomposed into progressively complex components, i.e., translation, similarity, affine, and projective motion models, and alignment is obtained with deliberatively selected suitable feature types and associated descriptors. Large convergence range is obtained by gradually constraining the search range of features in each stage. Notably, point and line features are jointly used and formulated in a RANSAC (random sample consensus) framework for robust estimation of a homography between low textured images. Further improvement is obtained with region based direct method. Experiments demonstrate superior alignment results of our approach to both gradient-based direct method and tradition point feature based alignment method
6548026
Automated Mosaics via Topology Inference
The authors present a complete approach for the automated construction of mosaics from images and video using topology inference, local and global alignment, and compositing.
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.
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.
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.
8733679
Stochastic Fluid Theory for P2P Streaming Systems
We develop a simple stochastic fluid model that seeks to expose the fundamental characteristics and limitations of P2P streaming systems. This model accounts for many of the essential features of a P2P streaming system, including the peers' realtime demand for content, peer churn (peers joining and leaving), peers with heterogeneous upload capacity, limited infrastructure capacity, and peer buffering and playback delay. The model is tractable, providing closed-form expressions which can be used to shed insight on the fundamental behavior of P2P streaming systems. The model shows that performance is largely determined by a critical value. When the system is of moderate-to-large size, if a certain ratio of traffic loads exceeds the critical value, the system performs well; otherwise, the system performs poorly. Furthermore, large systems have better performance than small systems since they are more resilient to bandwidth fluctuations caused by peer churn. Finally, buffering can dramatically improve performance in the critical region, for both small and large systems. In particular, buffering can bring more improvement than can additional infrastructure bandwidth.
2171095
Heterogeneous chip multiprocessors
Heterogeneous (or asymmetric) chip multiprocessors present unique opportunities for improving system throughput, reducing processor power, and mitigating Amdahl's law. On-chip heterogeneity allow the processor to better match execution resources to each application's needs and to address a much wider spectrum of system loads - from low to high thread parallelism - with high efficiency.
7623585
Low-Overhead, High-Speed Multi-core Barrier Synchronization
Whereas efficient barrier implementations were once a concern only in high-performance computing, recent trends in core integration make the topic relevant even for general-purpose CMPs. While the nature of CMP applications requires low-latency, the cost of low-latency barrier implementations using hardware-based techniques can be prohibitive for CMPs, where die area represents opportunities for throughput and yield. Similarly, whereas traditional multiprocessor barrier implementations were developed primarily for dedicated environments, scheduling and multi-programming on CMPs require more adaptable barrier implementations. 
 
In this paper, we present and evaluate three barrier implementations that are hybrids of software and dedicated hardware barriers and are specifically tailored for CMPs. The implementations leverage the unique characteristics of CMPs and provide low latency comparable to that of dedicated hardware networks at a fraction of the cost. The implementations also support adaptability, enabling efficient multi-programming and dynamic remapping of the barrier network.
6690431
Balanced Multithreading: Increasing Throughput via a Low Cost Multithreading Hierarchy
A simultaneous multithreading (SMT) processor can issue instructions from several threads every cycle, allowing it to effectively hide various instruction latencies; this effect increases with the number of simultaneous contexts supported. However, each added context on an SMT processor incurs a cost in complexity, which may lead to an increase in pipeline length or a decrease in the maximum clock rate. This paper presents new designs for multithreaded processors which combine a conservative SMT implementation with a coarse-grained multithreading capability. By presenting more virtual contexts to the operating system and user than are supported in the core pipeline, the new designs can take advantage of the memory parallelism present in workloads with many threads, while avoiding the performance penalties inherent in a many-context SMT processor design. A design with 4 virtual contexts, but which is based on a 2-context SMT processor core, gains an additional 26% throughput when 4 threads are run together.
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.