Selected Publications

This paper presents the advantages of a single-camera stereo omnidirectional system (SOS) in estimating egomotion in real-world environments. Dynamic conditions and the lack of features to track in the observable scene affect the pose estimation of all narrow-view systems. We compare the tracking accuracy and stability of the single-camera SOS versus an RGB-D device under various real circumstances. Our numerical evaluation is performed with respect to ground truth 3D data obtained from a motion capture system. The datasets and experimental results we provide are unique due to the nature of our catadioptric omnistereo rig, and the situations in which we captured these motion sequences. We have implemented a tracking system with proven correctness for both synthetic and real scenes. This implementation does not make any motion model assumptions, and it maintains a consistent configuration among the compared sensors. Our experimental outcomes confer the robustness in 3D metric visual odometry estimation that the single-camera SOS can achieve under normal and special conditions in which other perspective view systems such as RGB-D cameras would fail.
In under review, 2018.

We present direct multichannel tracking, an algorithm for tracking the pose of a monocular camera (visual odometry) using high-dimensional features in a direct image alignment framework.
In 3DV, 2017.

GUMS is a complete projection model for omnidirectional stereo vision systems. GUMS is based on the existing generalized unified model (GUM), which we extend for fixed baseline sensors.
In IROS, 2016.

We describe the design and 3D sensing performance of an omnidirectional stereo (omnistereo) vision system applied to Micro Aerial Vehicles (MAVs).
In Sensors, 2016.

All Publications

. Visual Odometry with a Single-Camera Stereo Omnidirectional System. In under review, 2018.

Details Video Code Dataset Project

. Direct Multichannel Tracking. In 3DV, 2017.

Details PDF Video Project Supplementary Materials

. GUMS: A Generalized Unified Model for Stereo Omnidirectional Vision. In IROS, 2016.

Details PDF Slides Video Project

. Design and Analysis of a Single-Camera Omnistereo Sensor for Quadrotor Micro Aerial Vehicles (MAVs). In Sensors, 2016.

Details PDF Code

. Autonomous Quadrotor Flight Using Onboard RGB-D Visual Odometry. In ICRA, 2014.

Details PDF Video Code

. 6-DoF Pose Localization in 3D Point-Cloud Dense Maps Using a Monocular Camera. In ROBIO, 2013.

Details PDF Video

. A Single-Camera Omni-Stereo Vision System for 3D Perception of Micro Aerial Vehicles (MAVs). In ICIEA, 2013.

Details PDF

. Incremental Registration of RGB-D Images. In ICRA, 2012.

Details PDF

. Generating near-spherical range panoramas by fusing optical flow and stereo from a single-camera folded catadioptric rig. In MVAP, 2011.

Details PDF

. Fusing Optical Flow and Stereo in a Spherical Depth Panorama Using a Single-Camera Folded Catadioptric Rig. In ICRA, 2011.

Details PDF


Visual Odometry with a Single-Camera Stereo Omnidirectional System

An extension of the generalized unified model (GUM) originally applied to a single omnidirectional view.

Direct Multichannel Tracking

An extension of the semi-dense visual odometry (camera pose tracking) originally applied to a single grayscale image by the state-of-the-art Large-Scale Direct (LSD) SLAM.

GUMS: Generalized Unified Model for Stereo Omnidirectional Vision

An extension of the generalized unified model (GUM) originally applied to a single omnidirectional view.

Single-Camera Omnistereo Sensor for Quadrotor Micro Aerial Vehicles (MAVs)

A novel omnidirectional stereo sensor using a pair of hyperbolic mirrors and a single camera.


In 2011, a new intelligent ground vehicle CATA (City Autonomous Transportation Agent) was rebuilt to employ the ROS framework to participate in IGVC.


In 2010, our intelligent ground vehicle CityALIEN participated and won the IGVC Design Challenge.


I have quite a bit of experience teaching both kids and adults.

I was an adjunct lecturer at CUNY Lehman College for the Mathematics and Computer Science Dept., where I taught the following courses:

  • CIS 212 Microcomputer Architecture (Spring 2014-Spring 2016): This requirement course provides a broad study of architecture of microcomputer systems with emphasis on CPU functionality, system bus & memory design and performance, secondary storage technologies and management, input/output peripherals (display and printer technologies), and network technologies. The course follows the Systems Architecture textbook by Stephen D. Burd.

  • CMP 230 Programming Methods I (Fall 2013): Introduced freshman students to structured computer programming using Python, a modern high-level programming language. Programming constructs such as console I/O, data types, variables, control structures, iteration, data structures, function definitions and calls, parameter passing, functional decomposition, object oriented programming, debugging and documentation techniques.

I have also taught STEM summer courses, such as:

  • STEM Robotics (Summer 2015) sponsored by the CUNY City College STEM Institute: In this intensive program for selective high school students who learned fundamentals of mobile robotics using the Raspberry Pi (computer) and Python programming language in order to actuate motors and poll sensor data (e.g. ultrasonic, infrared) and various electronic components. Ultimately, participants built robots to compete in an autonomous robot sumo tournament

As well as teaching middle school in NYC:

In the summer of 2013, I participated in a two-week NSF-sponsored CUNY Science Now Professional Development Workshop.


  • omnistereo AT gmail
  • Grove School of Engineering, Room T539, City College of New York, New York, NY 10031, USA