12562860
Shapeme histogram projection and matching for partial object recognition
Histograms of shape signature or prototypical shapes, called shapemes, have been used effectively in previous work for 2D/3D shape matching and recognition. We extend the idea of shapeme histogram to recognize partially observed query objects from a database of complete model objects. We propose representing each model object as a collection of shapeme histograms and match the query histogram to this representation in two steps: 1) compute a constrained projection of the query histogram onto the subspace spanned by all the shapeme histograms of the model and 2) compute a match measure between the query histogram and the projection. The first step is formulated as a constrained optimization problem that is solved by a sampling algorithm. The second step is formulated under a Bayesian framework, where an implicit feature selection process is conducted to improve the discrimination capability of shapeme histograms. Results of matching partially viewed range objects with a 243 model database demonstrate better performance than the original shapeme histogram matching algorithm and other approaches.
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.
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.
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.
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.
9616848
Core architecture optimization for heterogeneous chip multiprocessors
Previous studies have demonstrated the advantages of single-ISA heterogeneous multi-core architectures for power and performance. However, none of those studies examined how to design such a processor; instead, they started with an assumed combination of pre-existing cores. This work assumes the flexibility to design a multi-core architecture from the ground up and seeks to address the following question: what should be the characteristics of the cores for a heterogeneous multi-processor for the highest area or power efficiency? The study is done for varying degrees of thread-level parallelism and for different area and power budgets. The most efficient chip multiprocessors are shown to be heterogeneous, with each core customized to a different subset of application characteristics — no single core is necessarily well suited to all applications. The performance ordering of cores on such processors is different for different applications; there is only a partial ordering among cores in terms of resources and complexity. This methodology produces performance gains as high as 40%. The performance improvements come with the added cost of customization.
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.
1111313
Resist pattern peeling assessment in DUV chemically amplified resist
As device size shrinks resist line peeling becomes more challenging. In this paper we studied the resist pattern peeling based on resist processing parameters and type of bottom antireflective coating (BARC), for patterning trench structures with different duty ratios, in copper and low k dual damascene process. To minimize resist poisoning in dual damascene process, acetal-based resist was used. Significant improvement in via poisoning was observed with this chemistry as compared to environmentally stable chemically amplified resist chemistry but at the cost of pattern peeling. In order to solve pattern peeling problem we tried to analyze key factors such as compatibility with BARC, post-exposure bake, BARC curing, adhesion and their effects. Pitch dependency on pattern peeling margin is observed.
752417
Single-ISA Heterogeneous Multi-Core Architectures: The Potential for Processor Power Reduction
This paper proposes and evaluates single-ISA heterogeneousmulti-core architectures as a mechanism to reduceprocessor power dissipation. Our design incorporatesheterogeneous cores representing different points inthe power/performance design space; during an application'sexecution, system software dynamically chooses themost appropriate core to meet specific performance andpower requirements.Our evaluation of this architecture shows significant energybenefits. For an objective function that optimizes forenergy efficiency with a tight performance threshold, for 14SPEC benchmarks, our results indicate a 39% average energyreduction while only sacrificing 3% in performance.An objective function that optimizes for energy-delay withlooser performance bounds achieves, on average, nearly afactor of three improvement in energy-delay product whilesacrificing only 22% in performance. Energy savings aresubstantially more than chip-wide voltage/frequency scaling.
65135986
Model dependent inference of three-dimensional information from a sequence of two-dimensional images
In order to autonomously navigate through a complex environment, a mobile robot requires sensory feedback. This feedback will typically include the 3D motion and location of the robot and the 3D structure and motion of obstacles and other environmental features. The general problem considered in this thesis is how this 3D information may be obtained from a sequence of images generated by a camera mounted on a mobile robot. 
The first set of algorithms developed in this thesis are for robust determination of the 3D pose of the mobile robot from a matched set of model and image landmark features. Least-squares techniques for point and line tokens, which minimize both rotation and translation simultaneously are developed and shown to be far superior to the earlier techniques which solved for rotation first and then translation. However, least-squares techniques fail catastrophically when outliers (or gross errors) are present in the match data. Outliers arise frequently due to incorrect correspondences or gross errors in the 3D model. Robust techniques for pose determination are developed to handle data contaminated by fewer than 50.0% outliers. 
To make the model based approach widely applicable, it is necessary to be able to automatically build the landmark models. The approach adopted in this thesis is one of model extension and refinement. A partial model of the environment is assumed to exist and this model is extended over a sequence of frames. As will be shown in the experiments, the prior knowledge of the small partial model greatly enhances the robustness of the 3D structure computations. The initial 3D model may have errors and these too are refined over the sequence of frames. 
Finally, the sensitivity of pose determination and model extension to incorrect estimates of camera parameters is analyzed. It is shown that for small field of view systems, offsets in the image center do not significantly affect the location of the camera and the location of new 3D points in a world coordinate system. Errors in the focal length significantly affect only the component of translation along the optical axis in the pose computation.