Searcharxiv⌕ Search

arXiv subjects

Ramanathan Subramanian

Publications and source records attributed to Ramanathan Subramanian.

42 records · Page 3Linked to original sources
arXiv2017

Gender and Emotion Recognition with Implicit User Signals

We examine the utility of implicit user behavioral signals captured using low-cost, off-the-shelf devices for anonymous gender and emotion recognition. A user study designed to examine male and female sensitivity to facial emotions confirms that females recognize (especially negative) emotions quicker and more accurately than men, mirroring prior findings. Implicit viewer responses in the form of EEG brain signals and eye movements are then examined for existence of (a) emotion and gender-specific patterns from event-related potentials (ERPs) and fixation distributions and (b) emotion and gender discriminability. Experiments reveal that (i) Gender and emotion-specific differences are observable from ERPs, (ii) multiple similarities exist between explicit responses gathered from users and their implicit behavioral signals, and (iii) Significantly above-chance ($\approx$70%) gender recognition is achievable on comparing emotion-specific EEG responses-- gender differences are encoded best for anger and disgust. Also, fairly modest valence (positive vs negative emotion) recognition is achieved with EEG and eye-based features.

cs.HC↗
arXiv2017

Software-Defined Network Controlled Switching between Millimeter Wave and Terahertz Small Cells

Small cells are a cost-effective way to reliably expand network coverage and provide significantly increased capacity for end users. The ultra-high bandwidth available at millimeter (mmWave) and Terahertz (THz) frequencies can effectively realize short-range wireless access links in small cells enabling potential uses cases such as driver-less cars, data backhauling and ultra-high-definition infotainment services. This paper describes a new software defined network (SDN) framework for vehicles equipped with transceivers capable of dynamically switching between THz and mmWave bands. We present a novel SDN controlled admission policy that preferentially handoffs between the mmWave and THz small cells, accommodates asymmetric uplink/downlink traffic, performs error recovery and handles distinct link states that arise due to motion along practical vehicular paths. We then analytically derive the resulting capacity of such a small cell network by accounting for the channel characteristics unique to both these spectrum bands, relative distance and the contact times between a given transceiver pair. We then formulate the optimal procedure for scheduling multiple vehicles at a given infrastructure tower, with regards to practical road congestion scenarios. The search for the optimal schedule is shown to be a NP-hard problem. Hence, we design a computationally-feasible polynomial-time scheduling algorithm that runs at the SDN controller and compare its performance against the optimal procedure and random access. Additionally, we present a simulation-based case study for the use case of data center backhauling in Boston city to showcase the benefits of our approach.

cs.NI↗
arXiv2016

High-Level System Design of IEEE 802.11b Standard-Compliant Link Layer for MATLAB-Based SDR

Software defined radio (SDR) allows unprecedented levels of flexibility by transitioning the radio communication system from a rigid hardware platform to a more user-controlled software paradigm. However, it can still be time consuming to design and implement such SDRs as they typically require thorough knowledge of the operating environment and a careful tuning of the program. In this work, our contribution is the design of a bidirectional transceiver that runs on the commonly used USRP platform and implemented in MATLAB using standard tools like MATLAB Coder and MEX to speed up the processing steps. We outline strategies on how to create a state-action based design, wherein the same node switches between transmitter and receiver functions. Our design allows optimal selection of the parameters towards meeting the timing requirements set forth by various processing blocks associated with a DBPSK physical layer and CSMA/CA/ACK MAC layer so that all operations remain functionally compliant with the IEEE 802.11b standard for the 1 Mbps specification. The code base of the system is enabled through the Communications System Toolbox and incorporates channel sensing and exponential random back-off for contention resolution. The current work provides an experimental testbed that enables creation of new MAC protocols starting from the fundamental IEEE 802.11b standard. Our design approach guarantees consistent performance of the bi-directional link, and the three node experimental results demonstrate the robustness of the system in mitigating packet collisions and enforcing fairness among nodes, making it a feasible framework in higher layer protocol design.

cs.NI↗
arXiv2016

PET: An Eye-tracking Dataset for Animal-centric PASCAL Object Classes

We present the Pascal animal classes Eye Tracking database. Our database comprises eye movement recordings compiled from forty users for the bird, cat, cow, dog, horse and sheep {trainval} sets from the VOC 2012 image set. Different from recent eye-tracking databases such as \cite{kiwon_cvpr13_gaze,PapadopoulosCKF14}, a salient aspect of PET is that it contains eye movements recorded for both the free-viewing and visual search task conditions. While some differences in terms of overall gaze behavior and scanning patterns are observed between the two conditions, a very similar number of fixations are observed on target objects for both conditions. As a utility application, we show how feature pooling around fixated locations enables enhanced (animal) object classification accuracy.

cs.HC↗
arXiv2015

SALSA: A Novel Dataset for Multimodal Group Behavior Analysis

Studying free-standing conversational groups (FCGs) in unstructured social settings (e.g., cocktail party ) is gratifying due to the wealth of information available at the group (mining social networks) and individual (recognizing native behavioral and personality traits) levels. However, analyzing social scenes involving FCGs is also highly challenging due to the difficulty in extracting behavioral cues such as target locations, their speaking activity and head/body pose due to crowdedness and presence of extreme occlusions. To this end, we propose SALSA, a novel dataset facilitating multimodal and Synergetic sociAL Scene Analysis, and make two main contributions to research on automated social interaction analysis: (1) SALSA records social interactions among 18 participants in a natural, indoor environment for over 60 minutes, under the poster presentation and cocktail party contexts presenting difficulties in the form of low-resolution images, lighting variations, numerous occlusions, reverberations and interfering sound sources; (2) To alleviate these problems we facilitate multimodal analysis by recording the social interplay using four static surveillance cameras and sociometric badges worn by each participant, comprising the microphone, accelerometer, bluetooth and infrared sensors. In addition to raw data, we also provide annotations concerning individuals' personality as well as their position, head, body orientation and F-formation information over the entire event duration. Through extensive experiments with state-of-the-art approaches, we show (a) the limitations of current methods and (b) how the recorded multiple cues synergetically aid automatic analysis of social interactions. SALSA is available at http://tev.fbk.eu/salsa.

cs.CV↗