Detecting and removing visual distractors for video aesthetic enhancement

Personal videos often contain visual distractors, which are objects that are accidentally captured that can distract viewers from focusing on the main subjects. We propose a method to automatically detect and localize these distractors through learning from a manually labeled dataset. To achieve spatially and temporally coherent detection, we propose extracting features at the Temporal-Superpixel (TSP) level using a traditional SVM-based learning framework. We also experiment with end-to-end learning using Convolutional Neural Networks (CNNs), which achieves slightly higher performance than other methods. The classification result is further refined in a post-processing step based on graph-cut optimization. Experimental results show that our method achieves an accuracy of 81% and a recall of 86%. We demonstrate several ways of removing the detected distractors to improve the video quality, including video hole filling; video frame replacement; and camera path re-planning. The user study results show that our method can significantly improve the aesthetic quality of videos

Construction of α,α‐disubstituted α‐Amino Acid Derivatives via aza‐Morita‐Baylis‐Hillman Reactions of 2‐Aminoacrylates with Activated Olefins

A useful and convenient strategy for the synthesis of α,α‐disubstituted α‐amino acid (α‐AA) derivatives via aza‐Morita‐Baylis‐Hillman reaction of 2‐aminoacrylates with activated olefins has been developed. A variety of α‐AA derivatives containing an α‐amino tertiary center were synthesized in good to excellent yields. The kinetic profiles and calculated methyl anion affinity (MAA) values were employed to rationalize the reactivities of different Michael acceptors used in the reaction

Enhancement of thermophilic anaerobic sludge digestion by 70ºC pre-treatment : energy considerations

The objective of this work was to investigate the effect of a low temperature pre-treatment (70°C) on the thermophilic anaerobic digestion of sewage sludge. Experimental results were used for the calculation of theoretical energy balances of full-scale digesters with and without pre-treatment step. The 70°C sludge pre-treatment increased sludge solubilization by 10 times and enhanced volatile fatty acids generation. Biogas production increased up to 30-40% and methane content in biogas from 64 to 68-70%. Theoretical calculations showed that additional surplus energy production would be expected by incorporating a 70°C pre-treatment step to a thermophilic reactor

Physics perspectives of heavy-ion collisions at very high energy

Heavy-ion collisions at very high colliding energies are expected to produce a quark-gluon plasma (QGP) at the highest temperature obtainable in a laboratory setting. Experimental studies of these reactions can provide an unprecedented range of information on properties of the QGP at high temperatures. We report theoretical investigations of the physics perspectives of heavy-ion collisions at a future high-energy collider. These include initial parton production, collective expansion of the dense medium, jet quenching, heavy-quark transport, dissociation and regeneration of quarkonia, photon and dilepton production. We illustrate the potential of future experimental studies of the initial particle production and formation of QGP at the highest temperature to provide constraints on properties of strongly interaction matter.Comment: 35 pages in Latex, 29 figure