Object understanding in generalized video segmentation

Choudhuri, Anwesa

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https://hdl.handle.net/2142/129355 Copy

Description

Title

Object understanding in generalized video segmentation

Author(s)

Choudhuri, Anwesa

Issue Date

2024-07-10

Director of Research (if dissertation) or Advisor (if thesis)

• Chowdhary, Girish
• Schwing, Alexander Gerhard

Doctoral Committee Chair(s)

Chowdhary, Girish

Committee Member(s)

• Driggs-Campbell, Katherine
• Wang, Yuxiong

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

Generalized video segmentation, video understanding

Abstract

Spatio-temporal object representation is a key component in video understanding and is important for tasks like generalized video segmentation. Current methods often fail to represent objects spatio-temporally, by failing to capture the motion and interactions of objects over time, leading to identity switches, especially when objects are diverse and never seen before. This limits the generalizability of current methods. In this dissertation, we develop approaches to overcome this. We first develop AS-MOTS, a globally optimal tracker based on ‘assignment-space’ that improves tracking accuracy and enriches spatial object proposals temporally. We then develop CAROQ, an approach to generate spatio-temporally rich object proposals to unify closed-world video segmentation and seamlessly address tracking. Finally, we present OW-VISCapTor, a generalized approach that simultaneously detects, segments, and generates object-centric captions for both seen and previously unseen objects in a video.

Graduation Semester

2024-08

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/129355

Copyright and License Information

Copyright 2024 Anwesa Choudhuri

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