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.
26545951
Placement of scattering bars in binary and attenuated phase shift mask for damascene trench patterning
Abstract Scattering bars have been very effective technique to increase the common lithography process window for patterns with design rules 0.18 μm and below. This paper studies the placement of scattering bars in binary and attenuated phase shift mask in damascene trench patterning. Different partial coherence values are used to compare the scattering bar effect in binary and 8% attenuated phase shift mask. At low partial coherence ( σ ) the trench size has been found more sensitive to scattering bar parameters than at high σ . Scattering bar separation is found more effective than size to affect the trench critical dimension (CD). At low partial coherence a deep valley or ‘V’ shaped CD trend is found in scattering bar separation versus CD curve. CD dip is more using APSM as compared to binary mask. The process latitude is poor at valley as compared to top. Also, 3 sigma CD variation and range is higher at valley as compared to other separations of the scattering bars.
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.
23462768
A method for deep etching in dielectric films for 3D-chip and photonics applications
Abstract In this paper, RIE of thick undoped silicate glass (USG) films for various applications is described. Though moderate etch rates (∼0.4 μm/min) were achieved for USG film, process development was quite challenging due to stringent requirements of deep USG etching (>6 μm) and vertical profile. Alternatively, etch process with higher etch rate (1.0 μm/min) was also evaluated for profile angle and results were found not comparable to low etch rate process. However, low etch rate process was found to have tool limitations and an alternate method called ‘discrete etching’ was proposed and successfully verified. Promising results were obtained with etch depth (6 μm) and vertical profile (∼89.50°) in USG as well as SiON films. Based on the results discrete etching method was found to have provided advantage of unlimited capability for deep etching.
14117182
Independent motion detection in 3D scenes
Presents an algorithmic approach to the problem of detecting independently moving objects in 3D scenes that are viewed under camera motion. There are two fundamental constraints that can be exploited for the problem: (i) a two- (or multi-)view camera motion constraint (for instance, the epipolar/trilinear constraint), and (ii) a shape constancy constraint. Previous approaches to the problem either only used partial constraints or relied on dense correspondences or flow. We employ both of these fundamental constraints in an algorithm that does not demand a-priori availability of correspondences or flow. Our approach uses the plane-plus-parallax decomposition to enforce the two constraints. It is also demonstrated, for a class of scenes called sparse 3D scenes, in which genuine parallax and independent motions may be confounded, how the plane-plus-parallax decomposition allows progressive introduction and verification of the fundamental constraints. The results of applying the algorithm to some difficult sparse 3D scenes look promising.
13502244
Object Tracking with Bayesian Estimation of Dynamic Layer Representations
Decomposing video frames into coherent 2D motion layers is a powerful method for representing videos. Such a representation provides an intermediate description that enables applications such as object tracking, video summarization and visualization, video insertion, and sprite-based video compression. Previous work on motion layer analysis has largely concentrated on two-frame or multi-frame batch formulations. The temporal coherency of motion layers and the domain constraints on shapes have not been exploited. This paper introduces a complete dynamic motion layer representation in which spatial and temporal constraints on shape, motion and layer appearance are modeled and estimated in a maximum a-posteriori (MAP) framework using the generalized expectation-maximization (EM) algorithm. In order to limit the computational complexity of tracking arbitrarily shaped layer ownership, we propose a shape prior that parameterizes the representation of shape and prevents motion layers from evolving into arbitrary shapes. In this work, a Gaussian shape prior is chosen to specifically develop a near-real-time tracker for vehicle tracking in aerial videos. However, the general idea of using a parametric shape representation as part of the state of a tracker is a powerful one that can be extended to other domains as well. Based on the dynamic layer representation, an iterative algorithm is developed for continuous object tracking over time. The proposed method has been successfully applied in an airborne vehicle tracking system. Its performance is compared with that of a correlation-based tracker and a motion change-based tracker to demonstrate the advantages of the new method. Examples of tracking when the backgrounds are cluttered and the vehicles undergo various rigid motions and complex interactions such as passing, turning, and stop-and-go demonstrate the strength of the complete dynamic layer representation.
12569145
Building segmentation for densely built urban regions using aerial LIDAR data
We present a novel building segmentation system for densely built areas, containing thousands of buildings per square kilometer. We employ solely sparse LIDAR (Light/Laser Detection Ranging) 3D data, captured from an aerial platform, with resolution less than one point per square meter. The goal of our work is to create segmented and delineated buildings as well as structures on top of buildings without requiring scanning for the sides of buildings. Building segmentation is a critical component in many applications such as 3D visualization, robot navigation and cartography. LIDAR has emerged in recent years as a more robust alternative to 2D imagery because it acquires 3D structure directly, without the shortcomings of stereo in un- textured regions and at depth discontinuities. Our main technical contributions in this paper are: (i) a ground segmentation algorithm which can handle both rural regions, and heavily urbanized areas, where the ground is 20% or less of the data, (ii) a building segmentation technique, which is robust to buildings in close proximity to each other, sparse measurements and nearby structured vegetation clutter, and (Hi) an algorithm for estimating the orientation of a boundary contour of a building, based on minimizing the number of vertices in a rectilinear approximation to the building outline, which can cope with significant quantization noise in the outline measurements. We have applied the proposed building segmentation system to several urban regions with areas of hundreds of square kilometers each, obtaining average segmentation speeds of less than three minutes per km2 on a standard Pentium processor. Extensive qualitative results obtained by overlaying the 3D segmented regions onto 2D imagery indicate accurate performance of our system.
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.
1908016
Optimal peer selection for P2P downloading and streaming
In a P2P system, a client peer may select one or more server peers to download a specific file. In a P2P resource economy, the server peers charge the client for the downloading. A server peer's price would naturally depend on the specific object being downloaded, the duration of the download, and the rate at which the download is to occur. The optimal peer selection problem is to select, from the set of peers that have the desired object, the subset of peers and download rates that minimizes cost. In this paper we examine a number of natural peer selection problems for both P2P downloading and P2P streaming. For downloading, we obtain the optimal solution for minimizing the download delay subject to a budget constraint, as well as the corresponding Nash equilibrium. For the streaming problem, we obtain a solution that minimizes cost subject to continuous playback while allowing for one or more server peers to fail during the streaming process. The methodologies developed in this paper are applicable to a variety of P2P resource economy problems.