Researcher:
Altıok, Ozan Can

Profile Picture
ORCID

Job Title

Master Student

First Name

Ozan Can

Last Name

Altıok

Name

Name Variants

Altıok, Ozan Can

Email Address

Birth Date

Filters

2016 - 20173

Advanced Search

Filter by

Settings

Researcher Of Publications: search.filters.isAuthorOfPublication.b9e7e935-605a-47bf-9290-f9f666ef44d3

Search Results

Now showing 1 - 3 of 3
  • Placeholder
    PublicationMetadata only
    Semantic sketch-based video retrieval with autocompletion
    (Association for Computing Machinery, 2016) Tǎnase, Claudiu; Giangreco, Ivan; Rossetto, Luca; Schuldt, Heiko; Seddati, Omar; Dupont, Stéphane; N/A; Department of Computer Engineering; Altıok, Ozan Can; Sezgin, Tevfik Metin; Master Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 18632
    The IMOTION system is a content-based video search engine that provides fast and intuitive known item search in large video collections. User interaction consists mainly of sketching, which the system recognizes in real-time and makes suggestions based on both visual appearance of the sketch (what does the sketch look like in terms of colors, edge distribution, etc.) and semantic content (what object is the user sketching). The latter is enabled by a predictive sketch-based UI that identifies likely candidates for the sketched object via state-of-the-art sketch recognition techniques and offers on-screen completion suggestions. In this demo, we show how the sketch-based video retrieval of the IMOTION system is used in a collection of roughly 30,000 video shots. The system indexes collection data with over 30 visual features describing color, edge, motion, and semantic information. Resulting feature data is stored in ADAM, an efficient database system optimized for fast retrieval.
  • Placeholder
    PublicationMetadata only
    IMOTION – searching for video sequences using multi-shot sketch queries
    (Springer, 2016) Rossetto, Luca; Giangreco, Ivan; Heller, Silvan; Tănase, Claudiu; Schuldt, Heiko; Dupont, Stephane; Seddati, Omar; Department of Computer Engineering; N/A; N/A; Sezgin, Tevfik Metin; Altıok, Ozan Can; Sahillioğlu, Yusuf; Faculty Member; Master Student; PhD Student; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 18632; N/A; 215195
    This paper presents the second version of the IMOTION system, a sketch-based video retrieval engine supporting multiple query paradigms. Ever since, IMOTION has supported the search for video sequences on the basis of still images, user-provided sketches, or the specification of motion via flow fields. For the second version, the functionality and the usability of the system have been improved. It now supports multiple input images (such as sketches or still frames) per query, as well as the specification of objects to be present within the tar-get sequence. The results are either grouped by video or by sequence and the support for selective and collaborative retrieval has been improved. Special features have been added to encapsulate semantic similarity.
  • Thumbnail Image
    PublicationOpen Access
    Characterizing user behavior for speech and sketch-based video retrieval interfaces
    (Association for Computing Machinery (ACM), 2017) Department of Computer Engineering; Sezgin, Tevfik Metin; Altıok, Ozan Can; Faculty Member; Master Student; Department of Computer Engineering; College of Engineering; 18632; N/A
    From a user interaction perspective, speech and sketching make a good couple for describing motion. Speech allows easy specification of content, events and relationships, while sketching brings in spatial expressiveness. Yet, we have insufficient knowledge of how sketching and speech can be used for motion-based video retrieval, because there are no existing retrieval systems that support such interaction. In this paper, we describe a Wizard-of-Oz protocol and a set of tools that we have developed to engage users in a sketch-and speech-based video retrieval task. We report how the tools and the protocol fit together using "retrieval of soccer videos" as a use case scenario. Our software is highly customizable, and our protocol is easy to follow. We believe that together they will serve as a convenient and powerful duo for studying a wide range of multi-modal use cases.