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Real-time, Passive Non-Line-of-Sight Imaging with Thermal Camera by Exploiting Bidirectional Reflectance Distribution Function

UCLA researchers in the Department of Electrical and Computer Engineering have developed a Non-line-of-sight (NLOS) Imaging System using low cost thermal cameras that enable 3D recovery of NLOS heat source for imaging around corners.

Rear View Vehicle Classification Using Computer Vision

Professor Bir Bhanu and colleagues at the  University of California, Riverside, have  developed a robust vehicle classification system based  on video images from the rear-side view of a vehicle. This  system classifies a vehicle into one of four  classes: sedan, pick-up truck, SUV/minivan,  and unknown. The system validates detected moving objects by a simple frame differencing approach. Table I shows the false alarm percentages over the different methods used to classify vehicles. Table II shows that the UCR method has the highest accuracy when compared to other known methods.       Figure 1 is the Dynamic Bayesian Network structure created by extracting data from surveillance. In conjunction with the car being spotted the Left Tail Light (LTL), License Plate (LP), Right Tail Light (RTL), and Rear Dimensions (RD) are identified simultaneously and set within the Dynamic Bayesian Network to accurately classify and identify the vehicle.    

Lambda-Reservoir Computing

UCLA researchers in the Department of Electrical and Computer Engineering have developed a Spectral Reservoir Computer that processes data using nonlinear optical interactions.

Use of a Radiation Detector that Combines Virtual Frisch Grid and Cerenkov Readouts

Researchers at the University of California, Davis have developed a radiation detector for high energy photons that employs a transparent semiconductor with a high index of refraction to combine benefits of Virtual Frisch Grid devices and the readout of Cerenkov light.

Multifaceted III-Nitride Surface-Emitting Laser

Improved laser capability using III-Nitride VCSELs as the illumination source for sensing applications of a fluorescent sample.

Sub-Carrier Successive-Approximation Mm-Wave Radar For High-Resolution 3D Imaging

UCLA researchers in the Department of Electrical Engineering have developed a sub-carrier successive approximation radar (SAR) system with a sufficiently high accuracy to capture three-dimensional images of objects concealed either under the clothing of a person, or within small packages. 

External Cavity Laser Based Upon Metasurfaces

UCLA researchers in the Department of Electrical Engineering have developed a novel approach for terahertz (THz) quantum-cascade (QC) lasers to achieve scalable output power, high quality diffraction limited, and directive output beams.

Individual Identity Verified Through Device-Free, WiFi Based Framework

Researchers at the University of California, Davis have developed a device-free, WiFi based framework that can isolate individual identity, from a small group of users, simply by observing variations in WiFi signals through a user’s gait.

Facial Recognition & Vehicle Logo Super-Resolution System

Background: The video surveillance market is projected to grow annually at 17% and reach $42B by 2020. Video surveillance is a popular tool to track and monitor movement of people and vehicles to provide protection and discover information for investigations. Current technologies are competent in capturing images but not with high definition. Therefore, a more advanced security system that is smarter and multidimensional is needed.  Brief Description: UCR Researchers have developed a novel method and system for unified face representation for individual recognition in surveillance videos along with vehicle recognition. They extracted facial images from a video, generated an emotion avatar image (EAI) and computed features using their innovative algorithms. Low-resolution vehicle images can also be enhanced by using their super-resolution algorithms to produce high-resolution images. Existing technologies can only take frontal images but this new technology can handle out-of-plane, rotated images.

A Video Based Hierarchical Vehicle Classification System

Background: Transportation and vehicle classification systems are becoming smarter and more automated. For example, electronic toll collection systems have been introduced and drivers are not required to stop, eliminating road delays. New technologies have also been added to these systems that enable service providers to acquire data on what type of vehicles are utilizing their amenities as well as vehicle identification for safety & control purposes.  Brief Description: UCR Researchers have developed a method and system for vehicle classification using video imaging. This novel invention entails a vehicle ground clearance measurement system along with a video camera that captures a travelling vehicle and categorizes it into a vehicle class. The cameras on current methods and systems rely on side views of the vehicle, which can easily be obstructed by other vehicles.

Image Filtering Algorithm for Enhanced Noise Removal and Feature Preservation

UCLA researchers in the Department of Chemistry & Biochemistry have developed a novel image filtering algorithm that removes image noise while preserving image features with unprecedented fidelity.   

Low-Duty-Cycle Continuous-Wave Photoconductive Terahertz Imaging and Spectroscopy Systems

Professor Mona Jarrahi in the UCLA Department of Electrical Engineering has developed a technique for operating continuous-wave (CW) terahertz imaging and spectroscopy systems based on photoconductive terahertz sources and/or detectors that uses a low-duty-cycle optical pump, achieving high radiation powers and detection sensitivities without causing thermal breakdown, as well as higher quality image and spectra data.

Sensor-Assisted Facial Authentication System For Smartphones

Researchers at the University of California, Davis have developed a method using standard mobile device sensors assisting with facial authentication to overcome the limitations faced by current methods.

System And Method For Capturing Vital Vascular Fingerprint

Improved reliability of fingerprint authentication is achieved through a unique vascular fingerprint which increases accuracy and verifies liveness.

Ringer: A Program To Detect Molecular Motions By Automatic Electron Density Sampling

Ringer distinguishes flexible regions from rigid regions of biomolecules such as drug receptors. To assess the generality and significance of the weak secondary peaks of uniquely modeled residues, we ran Ringer on 402 high-resolution (<=1.5 Å) crystal structures from the Protein Data Bank. Omit electron-density maps were analyzed to reduce the effects of model bias. When applied after refinement is considered complete, Ringer discovers polymorphism at over 3.5 times the frequency that is currently modeled in the PDB. Multiple conformers are found for >18% of unbranched residues in a test set of 402 high-resolution structures, in addition to the 5.1% that are already modeled. More than a method for enhancing crystallographic refinement, however, Ringer is best used as a tool for systematically detecting low-occupancy structural features. The hidden conformational substates identified using Ringer provide clues to the functional roles of protein structural polymorphism and to assess the response of protein side chain distributions to perturbations including ligand binding, temperature changes and mutations. In calmodulin, for example, Ringer identifies side chains that undergo conformational population inversions and side-chain rigidification upon peptide binding, linking the structure to dynamic properties. Similarly, in human proline isomerase, Ringer was used to define the nature of a coupled conformational switch in the free-enzyme that defines motions that occur during turnover. In both cases, the alternate conformations identified by Ringer provided structural insights not available from any other experimental technique. Link to overview of Ringer software

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