A solution to the correspondence problem in multi-view imagery

This paper concerns the analysis of multi-view imagery in order to obtain a scen description and, specifically, the correspondence problem that occurs in this analysis. The required scene description in this case consists of the classes of the objects present in the scene and their parameters: position, size and orientation. The images are aerial photographs and the objects in the images are man-made objects, such as buildings, roads etc

International Society for Krishna Consciousness, Inc. v. Lee: The Public Forum Doctrine Falls to a Government Intent Standard

Since its inception, the public forum doctrine has maintained a byzantine existence. The Supreme Court has struggled to define the extent to which the First Amendment protects expressive activities in public places. Prior to developing a public forum doctrine, the Court used various means to limit government restrictions of expressive uses of public property. Since 1972, however, the Court has increasingly relied on categorical approaches to determine when members of the general public can use government-controlled property for communicative purposes

Model-Based Recognition and Parameter Estimation of Buildings from Multi-View Aerial Imagery Using Multi-Segmentation

This paper describes a system for analysis of aerial images of urban areas using multiple images from different viewpoints. In this paper the emphasis is on the discussion of the experimental evaluation using segmented images obtained by applying 3 different parameters in the segmentation-process. The proposed approach combines bottom-up and top-down processing. To evaluate statistically the performance of the system, a set of 50 realisations of 5 images from different viewpoints was used, which was generated by combining real and ray-traced images. The experiments show a significant improvement of reliability and accuracy if multi-segmentation is used in multi-view imagery, instead of single-segmentation

Relations between depressed mood and vocal parameters before, during and after sleep deprivation: a circadian rhythm study

The mechanism underlying improvement after total sleep deprivation (TSD) was studied in 14 major depressed patients. The suggestions that (1) circadian processes and/or (2) dimensions of arousal may play a role in the response to TSD were investigated. Diurnal variation of depressed mood and of mood- and arousal-related vocal parameters was studied in relation to the effect of TSD on depressed mood and vocal parameters. During 3 baseline days, during TSD and 2 days after TSD vocal parameters and depressed mood were assessed 6 and 3 times daily respectively. The mean fundamental frequency (frequency of vocal fold vibration, F0) (presumably reflecting aspects of arousal) as well as the range of the F0 (proposed to reflect sadness) showed a clear circadian pattern with a peak at about 4.00 p.m. TSD affected the circadian organization of the mean F0 and advanced the peak of the curve. After one night of subsequent sleep this effect disappeared. In addition, improvement after TSD coincided with an increase of the mean F0. The diurnal variation of mood before TSD predicted the mood response to TSD, whereas diurnal variation of vocal parameters did not. Moreover, circadian changes in vocal parameters were not related to changes in depressed mood. These findings suggest that the diurnal variations in mood and vocal parameters are regulated by different mechanisms. Data support the presumption that circadian as well as arousal processes are involved in the mood response to TSD. Circadian changes in vocal parameters due to TSD are not likely to reflect changes in the biological clock.

Interactive Augmentation of Voice Quality and Reduction of Breath Airflow in the Soprano Voice

SummaryIn 1985, at a conference sponsored by the National Institutes of Health, Martin Rothenberg first described a form of nonlinear source-tract acoustic interaction mechanism by which some sopranos, singing in their high range, can use to reduce the total airflow, to allow holding the note longer, and simultaneously enrich the quality of the voice, without straining the voice. (M. Rothenberg, “Source-Tract Acoustic Interaction in the Soprano Voice and Implications for Vocal Efficiency,” Fourth International Conference on Vocal Fold Physiology, New Haven, Connecticut, June 3–6, 1985.) In this paper, we describe additional evidence for this type of nonlinear source-tract interaction in some soprano singing and describe an analogous interaction phenomenon in communication engineering. We also present some implications for voice research and pedagogy

A solution to the correspondence problem in multi-view imagery

This paper concerns the analysis of multi-view imagery in order to obtain a scene description and, specifically, the correspondence problem that occurs in this analysis. The required scene description in this case consists of the classes of the objects present in the scene and their parameters: position, size and orientation. The images are aerial photographs and the objects in the images are man-made objects, such as buildings, roads etc. The goal of the complete system is the fully automatic analysis of aerial photographs of urban areas. The output of the system is a scene description that can be used to generate or update a GIS (Geo Information System). Up to now a system has been developed that performs this analysis on a single image [2, 3]. The advantage of using multi-view imagery compared to using single images is that (partly) occluded buildings may still be recognized, because they can be more clearly visible in other images acquired from a different viewpoint. However, the use of multi-view imagery complicates the analysis, because the objects in the different images have to be corresponded to each other. In this paper a solution to this correspondence problem is presented on object hypothesis level. First the image analysis system for single images is described in short. Then the system is extended for multiple images and the method for corresponding object hypotheses is presented. Finally, experiments and conclusions are given

Global intensity correction in dynamic scenes

Changing image intensities causes problems for many computer vision applications operating in unconstrained environments. We propose generally applicable algorithms to correct for global differences in intensity between images recorded with a static or slowly moving camera, regardless of the cause of intensity variation. The proposed intensity correction is based on intensity quotient estimation. Various intensity estimation methods are compared. Usability is evaluated with background classification as example application. For this application we introduced the PIPE error measure evaluating performance and robustness to parameter setting. Our approach retains local intensity information, is always operational and can cope with fast changes in intensity. We show that for intensity estimation, robustness to outliers is essential for dynamic scenes. For image sequences with changing intensity, the best performing algorithm (MofQ) improves foreground-background classification results up to a factor two to four on real data