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.

Modelization and analysis of the electric arc in low voltage circuit breakers

246 p.

Length-weight relationship of mudskippers (Gobiidae: Oxudercinae) in the coastal areas of Selangor, Malaysia

Parameters a and b of the length-weight relationship (LWR) were estimated for eleven species of mudskippers caught in the coastal areas of Selangor, Malaysia. The values of b ranged from 2.56 to 3.50 with the mean b equal to 2.95 (n=11; sd=0.302). A normal distribution of the calculated LWR exponent (b) was obtained.

Economic analysis of climate change adaptation strategies in selected coastal areas in Indonesia, Philippines and Vietnam

This report is an account of a cross-country study that covered Vietnam, Indonesia and the Philippines. Covering four sites (one each in Indonesia and Vietnam) and two sites in the Philippines, the study documented the impacts of three climate hazards affecting coastal communities, namely typhoon/flooding, coastal erosion and saltwater intrusion. It also analyzed planned adaptation options, which communities and local governments can implement, as well as autonomous responses of households to protect and insure themselves from these hazards. It employed a variety of techniques, ranging from participatory based approaches such as community hazard mapping and Focus Group Discussions (FGDs) to regression techniques, to analyze the impact of climate change and the behavior of affected communities and households.

Economic analysis of climate change adaptation strategies in selected coastal areas in Indonesia, Philippines and Vietnam

Climate change with its attendant geophysical hazards is well studied. A great deal of attention has gone into analyzing climate change impacts as well as searching out possible mitigating adaptive strategies. These matters are very real concerns, especially for coastal communities. Such communities are often the most vulnerable to climate change, since their citizens frequently live in abject poverty and have limited capacity to adapt to geophysical hazards. Their situation is further complicated by the prospect of dealing with a confluence of hazards in comparison with those in other ecosystems. Against this backdrop Worldfish and the Economy and Environment Program for Southeast Asia (EEPSEA) collaborated to implement the cross-country study “Climate Change Impacts, Vulnerability Assessments, Economic and Policy Analysis of Adaptation Strategies in Selected Coastal Areas in Indonesia, Philippines, and Vietnam”. As its title suggests the study covered selected sites in Vietnam, Indonesia and the Philippines. Employing a gamut of interdisciplinary methodologies -- ranging from community-based approaches such as community hazard mapping and focus group discussions (FGDs) to regression techniques -- the study documented the impacts from three climate hazards affecting coastal communities. These were typhoon/flooding, coastal erosion, and saltwater intrusion. The team also analyzed planned adaptation options suited to implementation by communities and local governments, augmenting autonomous responses of households to protect and insure themselves from these hazards.