I. The crystal structure of a new dimer of triphenylfluorocyclobutadiene. II. A low temperature refinement of the cyanuric triazide structure

I. THE CRYSTAL STRUCTURE OF A NEW DIMER OF TRIPHENYLFLUOROCYCLOBUTADIENE

The crystal structure of thermal isomer of the “head-to-head” dimer of triphenylfluorocyclobutadiene was determined by the direct method. The Σ₂ relationship involving the low angle reflections with the largest E’s were found and solved for the signs by the symbolic method of Zachariasen. The structure was seen in the electron density map and the E-map, and was refined antisotropically by the method of least squares. The residual R was 0.065.

The structure is a gem-difluorohexaphenyldihydropentalene. All of the phenyl groups are planar as it is the cyclopentadiene ring of the dihydropentalene skeleton. Overcrowding at the position of the flourines causes some deviations from the normal bond angles in the cyclopentene ring.

The list of observed and calculated structure factors on pages 32-34 will not be legible on the microfilm. Photographic copies may be obtained from the California Institute of Technology.

II. A LOW TEMPERATURE REFINEMENT OF THE CYANURIC TRIAZIDE STRUCTURE

The structure of cyanuric triazide was refined anisotropically by the method of least squares. Three-dimensional intensity data, which has been collected photographically with MoK_α radiation at -110˚C, were used in the refinement. The residual R was reduced to 0.081.

The structure is completely planar, and there is no significant bond alternation in the cyanuric ring. The packing of the molecules causes the azide groups to deviate from linearity by 8 degrees.

Computational modeling and psychophysics in low- and mid-level vision

This thesis addresses a series of topics related to the question of how people find the foreground objects from complex scenes. With both computer vision modeling, as well as psychophysical analyses, we explore the computational principles for low- and mid-level vision.

We first explore the computational methods of generating saliency maps from images and image sequences. We propose an extremely fast algorithm called Image Signature that detects the locations in the image that attract human eye gazes. With a series of experimental validations based on human behavioral data collected from various psychophysical experiments, we conclude that the Image Signature and its spatial-temporal extension, the Phase Discrepancy, are among the most accurate algorithms for saliency detection under various conditions.

In the second part, we bridge the gap between fixation prediction and salient object segmentation with two efforts. First, we propose a new dataset that contains both fixation and object segmentation information. By simultaneously presenting the two types of human data in the same dataset, we are able to analyze their intrinsic connection, as well as understanding the drawbacks of today’s “standard” but inappropriately labeled salient object segmentation dataset. Second, we also propose an algorithm of salient object segmentation. Based on our novel discoveries on the connections of fixation data and salient object segmentation data, our model significantly outperforms all existing models on all 3 datasets with large margins.

In the third part of the thesis, we discuss topics around the human factors of boundary analysis. Closely related to salient object segmentation, boundary analysis focuses on delimiting the local contours of an object. We identify the potential pitfalls of algorithm evaluation for the problem of boundary detection. Our analysis indicates that today’s popular boundary detection datasets contain significant level of noise, which may severely influence the benchmarking results. To give further insights on the labeling process, we propose a model to characterize the principles of the human factors during the labeling process.

The analyses reported in this thesis offer new perspectives to a series of interrelating issues in low- and mid-level vision. It gives warning signs to some of today’s “standard” procedures, while proposing new directions to encourage future research.