most citedWhen Vehicles See Pedestrians with Phones:A Multi-Cue Framework for Recognizing Phone-based Activities of Pedestrians

3 citations · 3 across the 2 of their papers we have counts for

collaborators

8 papers

cs.CV2019

Forced Spatial Attention for Driver Foot Activity Classification

Akshay Rangesh, Mohan M. Trivedi

This paper provides a simple solution for reliably solving image classification tasks tied to spatial locations of salient objects in the scene. Unlike conventional image classific…

cs.CV2019

3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams

Walter Zimmer, Akshay Rangesh, Mohan Trivedi

In this paper, we focus on obtaining 2D and 3D labels, as well as track IDs for objects on the road with the help of a novel 3D Bounding Box Annotation Toolbox (3D BAT). Our open s…

cs.CV2018

Ground Plane Polling for 6DoF Pose Estimation of Objects on the Road

Akshay Rangesh, Mohan M. Trivedi

This paper introduces an approach to produce accurate 3D detection boxes for objects on the ground using single monocular images. We do so by merging 2D visual cues, 3D object dime…

cs.CV2018

HandyNet: A One-stop Solution to Detect, Segment, Localize & Analyze Driver Hands

Akshay Rangesh, Mohan M. Trivedi

Tasks related to human hands have long been part of the computer vision community. Hands being the primary actuators for humans, convey a lot about activities and intents, in addit…

cs.CV2018

Driver Hand Localization and Grasp Analysis: A Vision-based Real-time Approach

Siddharth, Akshay Rangesh, Eshed Ohn-Bar +1

Extracting hand regions and their grasp information from images robustly in real-time is critical for occupants' safety and in-vehicular infotainment applications. It must however,…

cs.CV2018

No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARs

Akshay Rangesh, Mohan M. Trivedi

Online multi-object tracking (MOT) is extremely important for high-level spatial reasoning and path planning for autonomous and highly-automated vehicles. In this paper, we present…