VIRTUAL VIEW SYNTHESIS BY NON-LOCAL MEANS FILTERING USING TEMPORAL DATA

A novel algorithm for Virtual View Synthesis based on Non-Local Means Filtering is presented in this paper. Apart from using the video frames from the nearby cameras and the corresponding per-pixel depth map, this algorithm also makes use of the previously synthesized frame. Simple and efficient, the algorithm can synthesize video at any given virtual viewpoint at a faster rate. In the process, the quality of the synthesized frame is not compromised. Experimental results prove the above mentioned claim. The subjective and objective quality of the synthesized frames are comparable to the existing algorithms.

A Suzaku view of IGR J16393-4643

The pulsar IGR J16393-4643 belongs to a class of highly absorbed supergiant high-mass X-ray binaries (HMXBs), characterized by a very high column density of absorbing matter. We present the results of simultaneous broad-band pulsation and spectrum analysis from a 44-ks Suzaku observation of the source. The orbital intensity profile created with the Swift Burst Alert Telescope (Swift-BAT) light curve shows an indication of IGR J16393-4643 being an eclipsing system with a short eclipse semi-angle theta(E) similar to 17 degrees. For a supergiant companion star with a 20-R-circle dot radius, this implies an inclination of the orbital plane in the range 39 degrees-57 degrees, whereas for a main-sequence B star as the companion with a 10-R-circle dot radius, the inclination of the orbital plane is in the range 60 degrees-77 degrees. Pulse profiles created for different energy bands have complex morphology, which shows some energy dependence and increases in pulse fraction with energy. We have also investigated broad-band spectral characteristics, phase-averaged spectra and resolving the pulse phase into peak and trough phases. The phase-averaged spectrum has a very high N-H(similar to 3 x 10(23) cm(-2)) and is described by a power law (Gamma similar to 0.9) with a high-energy cut-off above 20 keV. We find a change in the spectral index in the peak and trough phases, implying an underlying change in the source spectrum.

Dynamics of 3D view invariance in monkey inferotemporal cortex

Rotations in depth are challenging for object vision because features can appear, disappear, be stretched or compressed. Yet we easily recognize objects across views. Are the underlying representations view invariant or dependent? This question has been intensely debated in human vision, but the neuronal representations remain poorly understood. Here, we show that for naturalistic objects, neurons in the monkey inferotemporal (IT) cortex undergo a dynamic transition in time, whereby they are initially sensitive to viewpoint and later encode view-invariant object identity. This transition depended on two aspects of object structure: it was strongest when objects foreshortened strongly across views and were similar to each other. View invariance in IT neurons was present even when objects were reduced to silhouettes, suggesting that it can arise through similarity between external contours of objects across views. Our results elucidate the viewpoint debate by showing that view invariance arises dynamically in IT neurons out of a representation that is initially view dependent.

First Structural View of a Peptide Interacting with the Nucleotide Binding Domain of Heat Shock Protein 90

The involvement of Hsp90 in progression of diseases like cancer, neurological disorders and several pathogen related conditions is well established. Hsp90, therefore, has emerged as an attractive drug target for many of these diseases. Several small molecule inhibitors of Hsp90, such as geldanamycin derivatives, that display antitumor activity, have been developed and are under clinical trials. However, none of these tested inhibitors or drugs are peptide-based compounds. Here we report the first crystal structure of a peptide bound at the ATP binding site of the N-terminal domain of Hsp90. The peptide makes several specific interactions with the binding site residues, which are comparable to those made by the nucleotide and geldanamycin. A modified peptide was designed based on these interactions. Inhibition of ATPase activity of Hsp90 was observed in the presence of the modified peptide. This study provides an alternative approach and a lead peptide molecule for the rational design of effective inhibitors of Hsp90 function.

Limited-view light sheet fluorescence microscopy for three dimensional volume imaging

We propose and demonstrate a limited-view light sheet microscopy (LV-LSM) for three dimensional (3D) volume imaging. Realizing that longer and frequent image acquisition results in significant photo-bleaching, we have taken limited angular views (18 views) of the macroscopic specimen and integrated with maximum likelihood (ML) technique for reconstructing high quality 3D volume images. Existing variants of light-sheet microscopy require both rotation and translation with a total of approximately 10-fold more views to render a 3D volume image. Comparatively, LV-LSM technique reduces data acquisition time and consequently minimizes light-exposure by many-folds. Since ML is a post-processing technique and highly parallelizable, this does not cost precious imaging time. Results show noise-free and high contrast volume images when compared to the state-of-the-art selective plane illumination microscopy. (C) 2015 AIP Publishing LLC.

ON THE UTILITY OF CANONICAL CORRELATION ANALYSIS FOR DOMAIN ADAPTATION IN MULTI-VIEW HEADPOSE ESTIMATION

The utility of canonical correlation analysis (CCA) for domain adaptation (DA) in the context of multi-view head pose estimation is examined in this work. We consider the three problems studied in 1], where different DA approaches are explored to transfer head pose-related knowledge from an extensively labeled source dataset to a sparsely labeled target set, whose attributes are vastly different from the source. CCA is found to benefit DA for all the three problems, and the use of a covariance profile-based diagonality score (DS) also improves classification performance with respect to a nearest neighbor (NN) classifier.