13458811
Discovering class specific composite features through discriminative sampling with Swendsen-Wang Cut
This paper proposes a novel approach to discover a set of class specific ldquocomposite featuresrdquo as the feature pool for the detection and classification of complex objects using AdaBoost. Each composite feature is constructed from the combination of multiple individual features. Unlike previous works that design features manually or with certain restrictions, the class specific features are selected from the space of all combinations of a set of individual features. To achieve this, we first establish an analogue between the problem of discriminative feature selection and generative image segmentation, and then draw discriminative samples from the combinatory space with a novel algorithm called discriminative generalized Swendsen-Wang cut. These samples form the initial pool of features, where AdaBoost is applied to learn a strong classifier combining the most discriminative composite features. We demonstrate the efficacy of our approach by comparing with existing detection algorithms for finding people in general pose.
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.
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.
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.
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.
27240142
Two optimal peer selection problems
Many peer computers today participate in peer-to-peer file sharing applications in which the computers contribute storage and bandwidth resources. Of course, applications can only harness the resource pool if peers make available their surplus resources to them. It is widely documented, however, that the P2P systems are havens for "free riders": a significant fraction of users do not contribute any resources, and a minute fraction of users contribute the majority of the resources. Clearly, to improve the performance of existing P2P file sharing systems, and to enable new classes of P2P applications, a compelling incentive system needs to be put in place.
15134584
Replication of Biomolecular Techniques for Implementing Intelligent Systems
In this paper, it has been shown that computational jobs, such as encoding of input data and AND, OR operation, can work on the computers (by using computer databases and algorithms for the purpose of speeding up and enhancing biological research). By combining more complex functions, more complex molecular programs for gene analysis can be constructed. It is expected an in vivo (i.e. inside cellular life forms) computer will be realized from this technology, which detects the cell state through gene expression patterns, and controls the cell conditions with output RNA (ribose nucleic acid). The replication of biomolecular techniques based upon DNA (deoxyribose nucleic acid) architecture has been proposed. It may provide a powerful tool for both research and clinical applications. To develop functional supra-molecular systems, where sequence-programmable and evolvable molecular systems have been constructed as cell-free chemical systems using biomolecules such as DNA and proteins based on the integration of electronics, computer science, IT (information technology), mathematical and statistical tools. This paper is organised into four parts: part I describes the functioning and encoding processes of DNA computers, which are implemented using a traveling salesman problem (as in artificial intelligent systems) and single shortest path routing approach (as in computer networks) using object-oriented approach of software development, part II presents database integration with DNA using client-server technologies of Web design, part III discusses the implications of DNA for computer and network security, and part IV investigates and shows the results with the use of above mentioned approaches.
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.
8538452
Conjoined-Core Chip Multiprocessing
Chip Multiprocessors (CMP) and Simultaneous Multi-threading (SMT) are two approaches that have been proposed to increase processor efficiency. We believe these two approaches are two extremes of a viable spectrum. Between these two extremes, there exists a range of possible architectures, sharing varying degrees of hardware between processors or threads. This paper proposes conjoined-core chip multiprocessing - topologically feasible resource sharing between adjacent cores of a chip multiprocessor to reduce die area with minimal impact on performance and hence improving the overall computational efficiency. It investigates the possible sharing of floating-point units, crossbar ports, instruction caches, and data caches and details the area savings that each kind of sharing entails. It also shows that the negative impact on performance due to sharing is significantly less than the benefits of reduced area. Several novel techniques for intelligent sharing of the hardware resources to minimize performance degradation are presented.