47117010
Stylizing 2.5-D video
In recent years considerable interest has been given to non-photorealistic rendering of photographs, video, and 3D models for illustrative or artistic purposes. Conventional 2D inputs such as photographs and video are easy to create and capture, while 3D models allow for a wider variety of stylization techniques, such as cross-hatching. In this paper, we propose using video with depth information (2.5-D video) to combine the advantages of 2D and 3D input. 2.5-D video is becoming increasingly easy to capture, and with the additional depth information, stylization techniques that require shape information can be applied. However, because 2.5-D video contains only limited shape information and 3D correspondence over time is unknown, it is difficult to create temporally coherent stylized animations directly from raw 2.5-D video. In this paper, we present techniques for processing 2.5-D video to overcome these drawbacks, and demonstrate several styles that can be created using these techniques.
41028764
Large environment rendering using plenoptic primitives
One of the most difficult tasks in computer graphics is to enable virtual walkthroughs in very large and complicated environments that are photorealistic, seamless, and in real time. Current image-based rendering techniques, while capable of photorealism and interactive speeds, have failed in practice to extend to visualizations of such environments. We demonstrate an approach that defines a virtual walkthrough experience using plenoptic primitives (PPs). A PP can be any type of local visual experience: 360/spl deg/ static panorama, panoramic video (PV), lumigraph/light field representation, or concentric mosaics (CMs). By combining them judiciously, user experience can be authored with significantly reduced effort while maintaining high-quality user experience. We illustrate our technique on synthetic and real environments using PVs and CMs and show how the problem of achieving smooth transitions among PVs and CMs can be solved by using position-dependent local geometries.
122813254
Shape Ambiguities in Structure From Motion
This paper examines the fundamental ambiguities and uncertainties inherent in recovering structure from motion. By examining the eigenvectors associated with null or small eigenvalues of the Hessian matrix, we can quantify the exact nature of these ambiguities and predict how they affect the accuracy of the reconstructed shape. Our results for orthographic cameras show that the bas-relief ambiguity is significant even with many images, unless a large amount of rotation is present. Similar results for perspective cameras suggest that three or more frames and a large amount of rotation are required for metrically accurate reconstruction.
1332259
On the Motion and Appearance of Specularities in Image Sequences
Real scenes are full of specularities (highlights and reflections), and yet most vision algorithms ignore them. In order to capture the appearance of realistic scenes, we need to model specularities as separate layers. In this paper, we study the behavior of specularities in static scenes as the camera moves, and describe their dependence on varying surface geometry, orientation, and scene point and camera locations. For a rectilinear camera motion with constant velocity, we study how the specular motion deviates from a straight trajectory (disparity deviation) and how much it violates the epipolar constraint (epipolar deviation). Surprisingly, for surfaces that are convex or not highly undulating, these deviations are usually quite small. We also study the appearance of specularities, i.e., how they interact with the body reflection, and with the usual occlusion ordering constraints applicable to diffuse opaque layers. We present a taxonomy of specularities based on their photometric properties as a guide for designing separation techniques. Finally, we propose a technique to extract specularities as a separate layer, and demonstrate it using an image sequence of a complex scene.
26233543
Appearance-Based Structure from Motion Using Linear Classes of 3-D Models
In this paper, we address the problem of recovering 3-D models from sequences of partly calibrated images with unknown correspondence. To that end, we integrate tracking, structure from motion with geometric constraints (specifically in the form of linear class models) in a single framework. The key to making the proposed approach work is the use of appearance-based model matching and refinement which updates the estimated correspondences on each iteration of the algorithm. Another key feature is the matching of a 3-D model directly with the input images without the conventional 2-step approach of stereo data recovery and 3-D model fitting. Initialization of the linear class model to one of the input images (the reference image) is currently partly manual.This synthesis and refine approach, or appearance-based constrained structure from motion (AbCSfm), is especially useful in recovering shapes of objects whose general structureis known but which may have little discernable texture in significant parts of their surfaces. We applied the proposed approach to 3-D face modeling from multiple images to create new 3-D faces for DECface, a synthetic talking head developed at Cambridge Research Laboratory, Digital Equipment Corporation. The DECface model comprises a collection of 3-D triangular and rectangular facets, with nodes as vertices. In recovering the DECface model, we assume that the sequence of images is taken with a camera with unknown focal length and pose. The geometric constraints used are of the form of linear combination of prototypes of 3-D faces of real people. Results of this approach show its good convergence properties and its robustness against cluttered backgrounds.
9867826
A multibaseline stereo system with active illumination and real-time image acquisition
We describe our implementation of a parallel depth recovery scheme for a four-camera multibaseline stereo in a convergent configuration. Our system is capable of image capture at video rate. This is critical in applications that require three-dimensional tracking. We obtain dense stereo depth data by projecting a light pattern of frequency modulated sinusoidally varying intensity onto the scene, thus increasing the local discriminability at each pixel and facilitating matches. In addition, we make most of the camera view areas by converging them at a volume of interest. Results show that we are able to extract stereo depth data that are, on the average, less than 1 mm in error at distances between 1.5 to 3.5 m away from the cameras.<<ETX>>
11955356
Automatic Segmentation of Words using Syllable Bigram Statistics
We present a syllable bigram model for segmenting a Korean sentence into words and correcting word-spacing errors in the spelling checker. We evaluated the system’s performance for automatic word segmentation, word-spacing error detection, and the word-splitting problem of the character recognition system at the end of a line.
205396452
Video dejittering by bake and shake
Video jittering occurs when the horizontal lines of video image frames are randomly displaced due to the corruption of synchronization signals or electromagnetic interference during video transmission. Inspired by the recent Bayesian/variational dejittering model of Shen (SIAM J. Appl. Math., vol. 64, pp. 1691-1708, 2004), in the current paper we propose a novel dejittering approach nicknamed 'bake-and-shake.' The bake step is to apply Perona-Malik type nonlinear diffusions to 'melt away' or heat up the jittered video frames, based upon which the shake step is able to optimally estimate the individual line jitters and renormalize the jittered images. Numerical implementation of the bake-and-shake algorithm as well as several computational results are presented.
32568915
Event Sentence Extraction in Korean Newspapers
Information extraction is to extract information about the main events in the text. This paper presents an event sentence extraction method in Korean newspapers for information extraction. Event sentences contain meaningful information such as the agent, the time and the place of an event. To extract these sentences, we acquire various features such as verbs, nouns, noun phrases, 3Ws, and their weights. And then, the system computes weights of sentences and extracts event sentences by our extraction algorithm. The experimental result shows the average precision of 86.1%.
5454614
Impact of FEC overhead on scalable video streaming
Forward-error correction (FEC) is used in many streaming applications for protecting multimedia data over lossy network paths. However, studies in the literature [1, 3, 4] report conflicting results on the benefits of FEC. To address this uncertainty, we study the performance of FEC-based streaming and provide additional insight into how FEC overhead rate affects the performance of scalable video streaming under dynamically changing network packet loss. Through analytical investigation, we derive the relationship between packet loss, FEC overhead, and utility of received video, and propose a simple control mechanism that adjusts the amount of FEC based on packet loss information. We find that our FEC control allows the application to maintain high end-user utility and achieve better quality of video at the receiver.
36602039
A low-power 1.85 GHz 32-bit carry lookahead adder using Dual Path All-N-Logic
We have developed Dual Path All-N-logic (DPANL) and applied to 32-bit adder design for higher performance. The speed enhancement is mainly due to reduced capacitance at each evaluation node of dynamic circuits. Post-layout simulation results show that this adder can operate at frequencies up to 1.85 GHz for 0.35 /spl mu/m 1P4M CMOS technology and is 32.4% faster than the adder using all-N-transistor (ANT). It also consumes 29.2% less power than the ANT adder. A 0.35 /spl mu/m CMOS chip has been fabricated and tested to verify the functionality and performance of the DPANL adder on silicon.