People and Topics

2019 Fall Schedule

All meetings are held in EE 013.

Time

Monday

Tuesday

Wednesday

Friday

11:00-12:00

Forest

Software Engineering

Image Database

12:30-13:30

Human Behavior

13:30-14:30

Drone

Crowdsourcing

Embedded 2

14:30-15:30

Embedded 1

15:30-16:30

17:30-18:20

VIP lecture (EE 129)

Due to the large number of team mebers, it is not possible changing the regular meeting time. If your schedule does not fit into a particular team, you have to move to another team.

Topics

Forest Inventory Analysis

Use computer vision to calculate the sizes of trees (called diameter at breath height, or DBH), recognize the species of trees, and their locations. For Fall 2019, the team has two major goals: (1) handle multiple trees in a single frame and (2) handle trees in a nautral forest.

The following images show the result from a distance sensor and the tree image (before and after denoising).

forest03 forest04 forest05

The following images show how the team measures the diameter at breath height.

forest00 forest01 forest02

Readings for new members:


Analysis of Drone Video

This project creates computer vision solutions recognizing objects captured by cameras mounted on drones. In Fall 2019, the team will create a set of video clips for the following purposes:

  • Construct three-dimensional geometries of objects: The video clips will capture cardboard boxes of different sizes, together with a wide range of objects and several with known sizes.

  • Detect and track multiple moving objects: The clips include moving objects. The drone itself is also moving. The purpose is to correctly identify these objects and track their movements.

  • Segmentation: Create pixel-wise labels of different objects.

  • Re-identify people: Determine whether the same person has been before.

This project is supported by NSF CNS-1925713

Readings for new members:


Embedded Vision 1

Recent progress in computer vision has focused primarily in general-purpose object detection using datasets with many (hundreds) categories of objects (such as humans, dogs, vehicles, furniture, buildings, etc.). For many applications, however, the number of possible objects can be limited. For example, inside an airport terminal, elephants or eagles are not expected. This project will use computer graphics to synthesize images and videos of these scenarios. The synthesized data is used to train computer vision running on embedded systems (also called edge devices). Doing so can reduce network traffic and make the system more scalable. Moreover, sensitive information (such as human faces) may be detected and protected before the data leaves the cameras.

Readings for new members:

Analyze Human Behavior in Video

The purpose of this team is to use real-time video analytics to detect dangerous behavior or safety violation in workplace (such as factories), raise alerts to prevent injury, or provide post-event analysis to prevent future occurrences. In Fall 2019, the team will focus on solving these problems in an indoor environment with multiple cameras:

  • Where are the people (including re-identifying the same person in different cameras)?

  • Where does each person face?

Readings


Software Engineering for Machine Learning

This project creates a process for developing reproducible software used in machine learning. In Fall 2019, the team’s focus is to create tools that faciliate code review. The tools analyze the histories of version control repositories and automatically identify possible defects within a pull request. The tools will also collect metrics relating to the code review.

Readings


Crowdsourcing

Computer vision is still not perfect and humans outperform computers in many situations. This team builds computer tools (human interfaces) for humans to identify unexpected properties (called “bias”) in data used to train computer programs. These tools are computer games and the players (crowds) describe the characteristics in the data.

Reading for new members:

crowdsource03 crowdsource02

crowdsource05 crowdsource04


Image Database

This system integrates computer vision and database. After the objects in images are detected, the information is stored in a database so that it is searchable. The team has built a prototype of the system processing multiple video streams simultaneously. The team will focus on improving the performance (scalability) for lower latency as well as investigating new storage systems.

Reading for new members:


Embedded Vision 2

This project investigates computer vision solutions that can perform the following tasks in an embedded computer (small enough to be inside a typical camera)

  • Obtain aggregate information (such as the number of people and their genders)

  • Detect faces

  • Encrypt the faces before sending the data to storage

The sensitive data (faces) never leaves the camera. Only authorized people with the decryption key can see the faces. The concept is illustrated below.

embeddedprivacy

Readings for new members:


Faculty

https://ag.purdue.edu/ProfileImages/dbarbara.jpg

David Michael Barbarash

Landscape Architecture, Purdue

https://engineering.purdue.edu/ResourceDB/ResourceFiles/image92690

Dave Cappelleri

Mechanical Engineering, Purdue

https://shuohanchen.files.wordpress.com/2019/02/shuohan-eps-converted-to.png?w=220&h=300

Shuo-Han Chen

Institute of Information Science, Academia Sinica

https://drive.google.com/uc?id=1EqxgXBuEQNiQ5pNVvg42AfWMFKByjKh1

Yung-Hsiang Lu

Electrical and Computer Engineering, Purdue

http://www.stat.purdue.edu/images/Faculty/thumbnail/varao-t.jpg

Vinayak Rao

Statistics, Purdue

https://drive.google.com/uc?id=19_-2sKwLTcjoBvjclB8tqlIA56k5QwUq

Guofan Shao

Professor, Forestry and Natural Resources, Purdue

https://avatars1.githubusercontent.com/u/651504?s=460&v=4

George K. Thiruvathukal

Computer Science, Loyola University Chicago.

http://www.stat.purdue.edu/~mdw/images/WardMFO.jpg

Mark Daniel Ward

Statistics, Purdue

https://ag.purdue.edu/ProfileImages/woeste.jpg

Keith E. Woeste

Forestry and Natural Resources, Purdue

https://www.cs.purdue.edu/people/images/small/faculty/mingyin.jpg

Ming Yin

Computer Science, Purdue

Members

Graduate Students

https://drive.google.com/uc?id=1YunKydNN7OS_vvBubbME4UykfjNh1CgA

Abhinav Goel: Doctoral Student, Improve Neural Networks’ Energy Efficiency

https://drive.google.com/uc?id=1GzpDueX6W2e4sx0OGfKm51cru34jyEvp

Sara Aghajanzadeh: Master Student, Detect Faces and Protect Privacy

https://drive.google.com/uc?id=1kIYIrkXnICIb2odq5WWGlsdCYv4fTpVU

Ryan Dailey: Master Student, Discover Network Cameras

https://drive.google.com/uc?id=1rtNrB-sPUJ6gllceGkgXex4gH11xZBmu

Caleb Tung: Doctoral Student, Using Contextual Information from Network Cameras to Improve and Evaluate Computer Vision Solutions

Undergraduate Students and 2019 Fall Teams

Image Database

Manage images and video so that they can be searched.

https://drive.google.com/uc?id=1F38cu70XGcBK2Z-HWBWdcYMAB9EClQZd

Sripath Mishra

Leader

https://drive.google.com/uc?id=1TfZn-I0Mk_lvY-cMontY8f1u9o5Zvc-y

Akshay Pawar

Co-leader

https://drive.google.com/uc?id=14OXZoRyCMuddHLMNwDz4NaWZcBq2FECA

Aditya Chakraborty

https://avatars3.githubusercontent.com/u/42661845?s=400&v=4

Hojoung Jang

https://drive.google.com/uc?id=1mjsB6izNO3fZF1E0umecBtGPN1t7nr_W

Ethan Lee

https://drive.google.com/uc?id=1xyr6ruLzgOX8H5H5SrBH7F_rJrRmwx7y

Vina Nguyen

Drone Video

Create datasets of drone video, recognize objects, estimate the sizes.

https://drive.google.com/uc?id=1QerVKIreOrBjZdoANEm4D0PlNcoyv79Q

Karthik Maiya

Leader

https://avatars3.githubusercontent.com/u/41479950?s=400&u=d252078920abb4e07f448b0c83c5ad14c32a1ef4&v=4

Jacob Harmon

Co-leader

https://i.ibb.co/4SB910F/20190617-180018.jpg

Avanish Subbiah

https://ca.slack-edge.com/T02T4RJGC-UMG8L5VAL-9052b09b9f0a-512

Rufat Imanov

https://drive.google.com/uc?id=1Yv1UB8v2LEjDsRCaCDilNzI68hoDAOXf

Katherine Sandys

https://i.imgur.com/c2lePxA.jpg

Justin Qualley

https://drive.google.com/uc?id=1M3PTWnGPrRkv2ntr_Furr-gh1VezKSL_

Victor Oduduabasi

Embedded Vision 1

Detect and encrypt faces to protect privacy using embedded computer.

https://drive.google.com/uc?id=1QE0RJBLacv9q-zbAvMf5JrZiHTx2htl_

Nobelle Tay

Leader

https://drive.google.com/uc?id=1C3jQYpkav8xVx80COdNjevix5kJ6kovh

Alex Xu

Co-leader

https://drive.google.com/uc?id=1aoA9YoFKVrmxOqf3kYcDr6USiYJSIFre

Raghu Selvaraj

https://drive.google.com/uc?id=1RUriBMS5XchLbjWiRWTwOO2XHCpCrf1R

Siddharth Srinivasan

Uday Thapar

https://media.licdn.com/dms/image/C5603AQFenyO-6ys8tA/profile-displayphoto-shrink_200_200/0?e=1574294400&v=beta&t=TCE4sLt89Yt6rdJzSgXqplfv1EV7k54wxdmhhBXK6Vc

Andrew Liu

https://drive.google.com/uc?id=1bZxvHiZ-H7ACq55FpJQqbJgj8NZjZlcb

Peter Huang

https://drive.google.com/uc?id=14-x3C-GKjClfZxBL2ZKI7ASRCTa26b9u

Youngsik Yoon

https://drive.google.com/uc?id=1aHllBZ0vsx_i_5n7P0IQG7ddCvaBcXjZ

Vaastav Arora

https://drive.google.com/uc?id=1iYwls-HfhBTdhomnDydzSjf-TqXVZ5XJ

Abhinav Goel

Doctoral Student

Embedded Vision 2

Identify the specific features (called distinctiveness) of different visual dataset. Use one dataset with many labels to help train machine models for another datasets with few labels.

https://drive.google.com/uc?id=1yUr73JBTlTG0LMew8pqVXA5csNggmuOX

Ashley Kim

Leader

CAM² Leader

https://drive.google.com/uc?id=1db-0VtllDb1sU5MeqnmOT9WKNMYsPy5z

Li Yon Tan

Co-leader

https://drive.google.com/uc?id=1RbbxJV5LEmUpPmfMcUU9V457Ww4wtN2t

Isha Ghodgaonkar

https://drive.google.com/uc?id=1Y7Ew3_OUSKDagQ7nOkRKOpYV1DhrPdi7

Fischer Bordwell

https://drive.google.com/uc?id=1PoRMRN5OFqoEFkuTo5IBZ3F1P07qDYBr

Kirthi Shankar Sivamani

https://drive.google.com/uc?id=1CNGW_coyipjeEnaR-53Da0HA0VYZ5dqU

Shuhao Xing

https://i.ibb.co/Y3yxZqX/CC2-DCFFF-3559-4727-9179-012-A628-AA161.jpg

Ziyad Alajmi

https://media.licdn.com/dms/image/C5603AQHUeEhI5uCp9Q/profile-displayphoto-shrink_200_200/0?e=1574899200&v=beta&t=f63UsWOOkgHQdK6rIRXOKJ4IShVMj1Csw1Aq5RQo1XM

Jackson Moffet

https://drive.google.com/uc?id=1atjrbMChToGU1xv_pKpQios6tEGRx6yM

Arnav Ballani

https://drive.google.com/uc?id=1bRRgMDNL1GA8tofA1orS_T47dp-thl4A

Chiche Tsai

https://drive.google.com/uc?id=1rtNrB-sPUJ6gllceGkgXex4gH11xZBmu

Caleb Tung

Doctoral Student

https://drive.google.com/uc?id=12g4phl1MKM0ajAALyiChi91guQAG9HtJ

Ryan Dailey

Masters Student

Teaching Assistant

Crowdsourcing for Data Bias

Use crowdsourcing to identify unintended bias in visual data and label data.

https://drive.google.com/uc?id=1BgdG9XYcrmdMtdSbePpp324jwdnwl_7p

Xiao Hu

Leader

https://drive.google.com/uc?id=1t-krvZinKrSk1YT8MRl8R6xoPUHpF8H7

Haobo Wang

Co-leader

https://drive.google.com/uc?id=12rvFZU_tTlGv1j80rsu-qzNliHma_ePJ

Somesh Dube

https://drive.google.com/uc?id=1Pik3biv3epBSKMobHHiqH8FcG9679ZSu

Kaiwen Yu

https://drive.google.com/uc?id=1mwPyRreZhhwa225Exj_fa5NaG7fV_V5q

Gore Kao

https://drive.google.com/uc?id=1u5dbejyw-62y5x6UPKEtPo3DFd4AtYCc

Anirudh Vegesana

Forest Inventory

Use computer vision to recognize tree species and estimate their sizes.

https://drive.google.com/uc?id=1WrLZtXkzgHDQbCC0XLX92C8a8rgS6yMd

Yezhi Shen

Leader

https://drive.google.com/uc?id=1wP9UDJhC13F_HkUZamnEa__jqSKusrJI

Minh Luong Nguyen

Co-leader

https://drive.google.com/uc?id=1GeeVgSnl4Fwf-rlIFlG5LuSohcMMIpTi

Nick Eliopoulos

CAM² Leader

https://i.ibb.co/Jxfdyb8/IMG-9250.jpg

Ya Ling Tsai

https://drive.google.com/uc?id=1_NsIm075R4bcxzz8pAfUqEmgLKoukgl8

Carolyn Tustin

Zoe Yang

https://i.ibb.co/y5GW8Hk/Selfie-2.jpg

David Jarufe

Human Behavior in Video

Understand human behavior and obtain aggregate information from video.

https://avatars3.githubusercontent.com/u/20303922?s=460&v=4

Moiz Rasheed

Leader

https://media.licdn.com/dms/image/C4E03AQHxkkJzNsdJIQ/profile-displayphoto-shrink_200_200/0?e=1574899200&v=beta&t=stc2udoK3PmShUEkelW3M-XpkalZ4mo9_iHmU7YERJ8

Ethan Glaser

Co-leader

https://drive.google.com/uc?id=1wzCPewNOxMyl3QBXAuwVUN_jeLqL8hnK

Wenxi Zhang

https://drive.google.com/uc?id=15MjIOEr5k1XvctTmnAM3yzy3JduC0MJm

Taher Dohadwala

https://i.ibb.co/89QDmQn/F7-AFDB67-67-B7-4-D85-BB04-3-D2-A5-C87-C14-A.jpg

Xiangyu Zhang

https://i.ibb.co/Zmf1XxM/IMG-20190816-WA0084.jpg

Amogh Shanbhag

https://drive.google.com/uc?id=1PJkmhvK36ClMnUlUpWYHRnaAD1bWw8LX

Seungjoon Rhie

https://drive.google.com/uc?id=12tE6ZiBLraMpfRq_C1HrqtN8Xv5PFEYY

Sara Aghajanzadeh

Masters Student

Software Engineering

Create procedure for developing high-quality and reproducible software.

https://drive.google.com/uc?id=1p5Ad8doE42SN57LXYTdsDtKOjmgGbPfG

Noah Curran

Leader

https://drive.google.com/uc?id=1UVhUsYnT9iUUBgFq6GAv6hFEtjxjZcND

Weiqing Huang

https://drive.google.com/uc?id=1IbObkujdVo4Y-ratjmZIHOdl43GYa58b

David Wood

https://media.licdn.com/dms/image/C4D03AQHGv7uBGa82HQ/profile-displayphoto-shrink_200_200/0?e=1574899200&v=beta&t=feI1rxEOBoBqfPS-apH1UP6erLCRYGoKrL4MFLA-RJ4

Connor Chadwick

https://i.postimg.cc/VkM4Gjjj/ezgif-com-crop.jpg

Ryan Firestone

https://i.imgur.com/KJNnNDT.jpg

Akhil Chinnakotla

https://media.licdn.com/dms/image/C5603AQFUK-Ix0GJN5w/profile-displayphoto-shrink_200_200/0?e=1574899200&v=beta&t=DKPkhPfHL7bYsoEPXrK7rSB9HRUcuEWwy20zMMlZU6c

Esteban Gorostiaga Zubizarreta

https://drive.google.com/uc?id=1XLmnG0oSQd_K9EFnKRg9uIQjE63eww9N

ZhiFei Chen

Midori Kisanuki

Alumni

Achinthya Soordelu

James Lee

He Li

Anthony Fennell

Jenil Patel

Ehren Marschall

Fengjian Pan

Nirmal Asokan

Sanghyun Cho

Shengli Sui

Woojin Kim

Ajay Gopakumar

Jiancheng Wang

Sitian Lu

Juncheng Tang

Milos Malesevic

Mina Guo

Hanyang Liu

Zhenming Zhang

Zaiwei Zhang

Jiaju Yue

Huanyi Guo

Jeanne Deng

Zhenming Zhao

Anthony Kang

Qingshuang Chen

Yuhao Chen

Borui Chen

Sriram Rangaramanujan

James Tay

Kyle Mcnulty

Seth Bontrager

Pranjit Kalita

Subhav Ramachandran

Everett Berry

Erik Rozolis

Bolun Zhang

Andrew Green

Yukun An

Daniel Dilger

Yexin Wang

Zhifan Zeng

Joseph Sweeney

Ryan Schlueter

John Laiman

Jay Patel

Yutong Huang

Yuxiang Zi

Zhanxiang Hua

Weizhi Li

Yash Pundlik

Ramyak Singh

Nanxin Jin

Kyle Martin

Hao Zou

Sam Yellin

Wenzhong Duan

Aparna Pidaparthi

Changyu Li

Deepika Aggrawal

Hanwen Huang

Hussni Mohd Zakir

Sihao Yin

Weiqing Huang

Christopher Jovanovic

Ahmed Kaseb

Wengyan Chan

Meera Haridasa

Deeptanshu Malik

Vadim Nikiforov

Matthew Fitzgerald

Youngsol Koh

Mehmet Alp Aysan

Cailey Farrell

Yifan Li

Lucas Neumann

Robert Gitau

Zhi Kai Tan

Spencer Huston

Mohamad Alani

Lucas Wiles

Yuxin Zhang

Chau Minh Nguyen

Shunqiao Huang

Minh Nguyen

Dhruv Swarup

Video by Current and Former Members