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Full-Text Articles in Physical Sciences and Mathematics
Person Identification From Streaming Surveillance Video Using Mid-Level Features From Joint Action-Pose Distribution, Binu M. Nair, Vijayan K. Asari
Person Identification From Streaming Surveillance Video Using Mid-Level Features From Joint Action-Pose Distribution, Binu M. Nair, Vijayan K. Asari
Vijayan K. Asari
We propose a real time person identification algorithm for surveillance based scenarios from low-resolution streaming video, based on mid-level features extracted from the joint distribution of various types of human actions and human poses. The proposed algorithm uses the combination of an auto-encoder based action association framework which produces per-frame probability estimates of the action being performed, and a pose recognition framework which gives per-frame body part locations. The main focus in this manuscript is to effectively combine these per-frame action probability estimates and pose trajectories from a short temporal window to obtain mid-level features. We demonstrate that these mid-level …
State Preserving Extreme Learning Machine For Face Recognition, Md. Zahangir Alom, Paheding Sidike, Vijayan K. Asari, Tarek M. Taha
State Preserving Extreme Learning Machine For Face Recognition, Md. Zahangir Alom, Paheding Sidike, Vijayan K. Asari, Tarek M. Taha
Vijayan K. Asari
Extreme Learning Machine (ELM) has been introduced as a new algorithm for training single hidden layer feed-forward neural networks (SLFNs) instead of the classical gradient-based algorithms. Based on the consistency property of data, which enforce similar samples to share similar properties, ELM is a biologically inspired learning algorithm with SLFNs that learns much faster with good generalization and performs well in classification applications. However, the random generation of the weight matrix in current ELM based techniques leads to the possibility of unstable outputs in the learning and testing phases. Therefore, we present a novel approach for computing the weight matrix …
Video-To-Video Pose And Expression Invariant Face Recognition Using Volumetric Directional Pattern, Vijayan K. Asari, Almabrok Essa
Video-To-Video Pose And Expression Invariant Face Recognition Using Volumetric Directional Pattern, Vijayan K. Asari, Almabrok Essa
Vijayan K. Asari
Face recognition in video has attracted attention as a cryptic method of human identification in surveillance systems. In this paper, we propose an end-to-end video face recognition system, addressing a difficult problem of identifying human faces in video due to the presence of large variations in facial pose and expression, and poor video resolution. The proposed descriptor, named Volumetric Directional Pattern (VDP), is an oriented and multi-scale volumetric descriptor that is able to extract and fuse the information of multi frames, temporal (dynamic) information, and multiple poses and expressions of faces in input video to produce feature vectors, which are …
Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari
Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari
Vijayan K. Asari
The initial framework for an electroencephalography (EEG) thought recognition software suite is developed, built, and tested. This suite is designed to recognize human thoughts and pair them to actions for controlling a robotic arm. Raw EEG brain activity data is collected using an Emotiv EPOC headset. The EEG data is processed through linear discriminant analysis (LDA), where an intended action is identified. The EEG classification suite is being developed to increase the number of distinct actions that can be identified compared to the Emotiv recognition software. The EEG classifier was able to correctly distinguish between two separate physical movements. Future …