King Fahd University of Petroleum and Minerals

Amer Ghazi Abdullah Binsaadoon

El-Sayed M El-Alfy

Methods, systems, and computer readable media for methods, computer readable media, and systems for automatic gender recognition including a phase quantization feature extraction method for automatic gender recognition in smart environments are described.

Automatic gender recognition utilizing gait energy image (GEI) images

Described is a novel method for feature extraction for automatic gait recognition. This method uses Multi-kernel Fuzzy-based Local Gabor Binary Pattern. From a captured gait video sequence, the gait period is determined then a gait energy image is constructed to represent the spatial-temporal variations during one motion cycle of the gait sequence. Then, each gait sequence is represented with a feature vector. The computation of this vector is conducted by first applying the 2D Gabor filter bank then encoding the variations in the Gabor magnitude using a multi-kernel fuzzy local binary pattern operator. Finally, gait classification is performed using a support vector machine.

Gait recognition system to identify walking subject

Multi-kernel fuzzy local Gabor feature extraction method for automatic gait recognition

Method for identifying a subject using gait analysis

Described herein is an apparatus and method for gait recognition. The apparatus includes circuitry that is configured to receive a gait sequence including a predetermined number of image frames of a subject. The received gait sequence is processed to generate a gait-energy-image (GEI). A plurality of Gabor filter responses is computed by convoluting the generated GEI with a bank of Gabor filters, wherein the filter bank includes a first predetermined number of unique scales, and a second predetermined number of unique orientations. Further, the circuitry is configured to partition, each Gabor filter response of the computed plurality of Gabor filter responses, into a predetermined number of overlapping regions and extract, a predetermined number of statistical features only from the overlapping regions, the extracted statistical features corresponding to texture content of the subject. The circuitry eventually recognizes the subject based on a classification of the extracted statistical features.

Identification method using partitioning of subject silhouettes

Described herein is an apparatus and method for gait recognition. The apparatus includes circuitry that is configured to receive a gait sequence including a predetermined number of image frames of a subject. The received gait sequence is processed to generate a gait-energy-image (GEI). A plurality of Gabor filter responses is computed by convoluting the generated GEI with a bank of Gabor filters, wherein the filter bank includes a first predetermined number of unique scales, and a second predetermined number of unique orientations. Further, the circuitry is configured to partition, each Gabor filter response of the computed plurality of Gabor filter responses, into a predetermined number of overlapping regions and extract, a predetermined number of statistical features only from the overlapping regions, the extracted statistical features corresponding to texture consent of the subject. The circuitry eventually recognizes the subject based on a classification of the extracted statistical features.

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Dhahran, Saudi Arabia

Amer Ghazi Abdullah Binsaadoon