Optimization of functionally graded metallic foam insulation under transient heat transfer conditions

of options to improve downstream analysis. Availability and Implementation: This open-source application was implemented in Perl and can be used as standalone version or accessed online through a user-friendly web interface. The source code, user help and additional information is available at

A methodology for detection and estimation in the analysis of golf putting

(The original publication is available at www.springerlink.com) A novel framework for 3D reconstruction and analysis of ancient inscriptions

Abstract We present a framework to segment cultural and natural features, given 3D aerial scans of a large urban area, and (optionally) registered ground level scans of the same area. This system provides a primary step to achieve the ultimate goal of detecting every object from a large number of varied categories, from antenna to power plants. Our framework first identifies local patches of the ground surface and roofs of buildings. This is accomplished by tensor voting that infers surface orientation from neighboring regions as well as local 3D points. We then group adjacent planar surfaces with consistent pose to find surface segments and classify them as either the terrain or roofs of buildings. The same approach is also applied to delineate vertical faces of buildings, as well as free-standing vertical structures such as fences. The inferred large structures are then used as geometric context to segment linear structures, such as power lines, and structures attached to walls and roofs from remaining unclassified 3D points in the scene. We demonstrate our system on real LIDAR datasets acquired from typical urban regions with areas of a few square kilometers each, and provide a quantitative analysis of performance using externally provided ground truth.

Evaluating multimedia features and fusion for example-based event detection

A non-stationary MRF model for image segmentation from a soft boundary map

Thermo-visual feature fusion for object tracking using multiple spatiogram trackers

W-operator window design by minimization of mean conditional entropy

Abstract We present a generic framework for enhanced active multi-sensing. We propose a coopetitive interaction approach, which combines the salient features of cooperation and competition with an aim to optimize the cooperation among sensors to achieve best results at the system level rather than redundantly implementing cooperation at each stage. We also employ model predictive control based forward state estimation method for counter-acting various delays faced in multi-sensor environments. The results obtained for two different visual surveillance adaptations with different number of cameras and different surveillance goals provide clear evidence for the improvements created by adoption of the proposed enhancements.