of a dissertation at the University of Miami. Dissertation supervised by Professor Mei-Ling Shyu. No. of pages in text. (153) The development in information science has enabled an explosive growth of ...
We propose a multimedia analytics solution for getting insight into image collections by extending the powerful analytic capabilities of pivot tables, found in the ubiquitous spreadsheets, to multimed...
We propose a multimedia analytics solution for getting insight in image collections by extending the powerful method of pivot tables, found in the ubiquitous spreadsheets, to multimedia. Our proposed ...
We propose a few-shot adaptation framework, which bridges zero-shot learning and supervised many-shot learning, for semantic indexing of image and video data. Few-shot adaptation provides robust param...
Video semantic indexing, which aims to detect objects, actions and scenes from video data, is one of important research topics in multimedia information processing. In the Text Retrieval Conference Vi...
Today's ubiquity of visual content as driven by the availability of broadband Internet, low-priced storage, and the omnipresence of camera equipped mobile devices conveys much of our thinking and feel...
This paper proposes an elastic spatial verification method for Instance Search, particularly for dealing with non-planar and non-rigid queries exhibiting complex spatial transformations. Different fro...
This paper addresses the fundamental question -- How do humans recognize complex events in videos? Normally, humans view videos in a sequential manner. We hypothesize that humans can make high-level i...
The subject of this thesis is about image and video representations for visual recognition. This thesis first focuses on image search, both for image and textual queries, and then considers the classi...
The rise of the social media and video streaming industry provided us a plethora of videos and their corresponding descriptive information in the form of concepts (words) and textual video captions. D...
The goal of this paper is to recognize actions in video without the need for examples. Different from traditional zero-shot approaches we do not demand the design and specification of attribute classi...
The goal of this paper is to recognize actions in video without the need for examples. Different from traditional zero-shot approaches we do not demand the design and specification of attribute classi...
The classification of imbalanced datasets has recently attracted significant attention due to its implications in several real-world use cases. The classifiers developed on datasets with skewed distri...
The Internet has been witnessing an explosion of video content. According to a Cisco study, video content is estimated to account for 80% of all the entire world's internet traffic by 2019. Video data...
Techniques for recognizing high-level events in consumer videos on the Internet have many applications. Systems that produced state-of-the-art recognition performance usually contain modules requiring...
Supervised learning using deep convolutional neural network has shown its promise in large-scale image classification task. As a building block, it is now well positioned to be part of a larger system...
Searching for matches to high-dimensional vectors using hard/soft vector quantization is the most computationally expensive part of various computer vision algorithms including the bag of visual word ...
Online discussion forums provide open workspace allowing users to share information, exchange ideas, address problems, and form groups. These forums feature multimodal posts and analyzing them require...
OF THE DISSERTATION INTEGRATING DEEP LEARNING WITH CORRELATION-BASED MULTIMEDIA SEMANTIC CONCEPT DETECTION by Hsin-Yu Ha Florida International University, 2015 Miami, Florida Professor Shu-Ching Chen,...
Nowadays, concept detection from multimedia data is considered as an emerging topic due to its applicability to various applications in both academia and industry. However, there are some inevitable c...