activity
20182026
most citedTraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions

233 citations · 780 across the 34 of their papers we have counts for

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Showing 2019Show all

11 papers · 1 filter

cs.CV2019★ 11 cited

The Liar's Walk: Detecting Deception with Gait and Gesture

Tanmay Randhavane, Uttaran Bhattacharya, Kyra Kapsaskis +3

We present a data-driven deep neural algorithm for detecting deceptive walking behavior using nonverbal cues like gaits and gestures. We conducted an elaborate user study, where we…

cs.RO2019★ 1 cited

Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs

Rohan Chandra, Tianrui Guan, Srujan Panuganti +4

We present a novel approach for traffic forecasting in urban traffic scenarios using a combination of spectral graph analysis and deep learning. We predict both the low-level infor…

eess.SP2019★ 1 cited

M3ER: Multiplicative Multimodal Emotion Recognition Using Facial, Textual, and Speech Cues

Trisha Mittal, Uttaran Bhattacharya, Rohan Chandra +2

We present M3ER, a learning-based method for emotion recognition from multiple input modalities. Our approach combines cues from multiple co-occurring modalities (such as face, tex…

cs.CV2019★ 44 cited

Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping

Uttaran Bhattacharya, Christian Roncal, Trisha Mittal +5

We present an autoencoder-based semi-supervised approach to classify perceived human emotions from walking styles obtained from videos or motion-captured data and represented as se…

cs.CV2019★ 102 cited

STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

Uttaran Bhattacharya, Trisha Mittal, Rohan Chandra +3

We present a novel classifier network called STEP, to classify perceived human emotion from gaits, based on a Spatial Temporal Graph Convolutional Network (ST-GCN) architecture. Gi…

cs.RO2019

GraphRQI: Classifying Driver Behaviors Using Graph Spectrums

Rohan Chandra, Uttaran Bhattacharya, Trisha Mittal +3

We present a novel algorithm (GraphRQI) to identify driver behaviors from road-agent trajectories. Our approach assumes that the road-agents exhibit a range of driving traits, such…