Face Recognition using Compressive Sensing
This paper deals with the Compressive Sensing implementation in the Face Recognition problem. Compressive Sensing is new approach in signal processing with a single goal to recover signal from small set of available samples. Compressive Sensing finds its usage in many real applications as it lowers the memory demand and acquisition time, and therefore allows dealing with huge data in the fastest manner. In this paper, the undersampled signal is recovered using the algorithm based on Total Variation minimization. The theory is verified with an experimental results using different percentage of signal samples.
Code (0)
등록된 구현이 없습니다.
Tasks
Compressive SensingFace RecognitionSimilar Papers 제목 키워드 기반
Multilinear Compressive Learning
Compressive Learning is an emerging topic that combines signal acquisition via compressive sensing and machine learning to perform inference tasks directly on a small number of measurements. Many data modalities naturall…
Compressive SensingFace RecognitionLicense Plate Recognition with Compressive Sensing Based Feature Extraction
License plate recognition is the key component to many automatic traffic control systems. It enables the automatic identification of vehicles in many applications. Such systems must be able to identify vehicles from imag…
Compressive SensingDimensionality ReductionGeneral ClassificationLicense Plate RecognitionGeneralized Optimization of High Capacity Compressive Imaging Systems
One of the greatest challenges in applying compressive sensing (CS) signal processing techniques to electromagnetic imaging applications is designing a sensing matrix that has good reconstruction capabilities. Compressiv…
Compressive SensingImage ReconstructionVocal Bursts Intensity PredictionOpenICS: Open Image Compressive Sensing Toolbox and Benchmark
We present OpenICS, an image compressive sensing toolbox that includes multiple image compressive sensing and reconstruction algorithms proposed in the past decade. Due to the lack of standardization in the implementatio…
BenchmarkingCompressive SensingCompressive Sensing via Convolutional Factor Analysis
We solve the compressive sensing problem via convolutional factor analysis, where the convolutional dictionaries are learned {\em in situ} from the compressed measurements. An alternating direction method of multipliers …
Compressive SensingGeneral Classification