ENHANCED SPATIO-TEMPORAL VIDEO COPY DETECTION BY COMBINING TRAJECTORY AND SPATIAL CONSISTENCY

Date

2014-10-30

Author

Ozkan, Savas
Esen, Ersin
Akar, Gözde

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

194
views

0
downloads

The recent improvements on internet technologies and video coding techniques cause an increase in copyright infringements especially for video. Frequently, image-based approaches appear as an essential solution due to the fact that joint usage of quantization-based indexing and weak geometric consistency stages give a capability to compare duplicate videos quickly. However, exploiting purely spatial content ignores the temporal variation of video. In this work, we propose a system that combines the state-of-the-art quantization-based indexing scheme with a novel trajectory-based geometric consistency on spatio-temporal features. This combination improves duplicate video matching task significantly. Briefly, spatial mean and variance of the trajectories are incorporated to establish a weak geometric consistency among pair of frames. To show the success of the proposed method, content-based video copy detection field is selected and TRECVID 2009 dataset is utilized. The experimental results show that constituting trajectory-based consistency on corresponding feature pairs outperforms the performances of merely utilizing spatiotemporal signature and visual signature with enhanced weak geometric consistency.

Subject Keywords

Spatio-temporal feature, Trajecotory-based consistency, Duplicate video search, Video copy detection

URI

https://hdl.handle.net/11511/52870

Conference Name

IEEE International Conference on Image Processing (ICIP)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

A PARAMETRIC VIDEO QUALITY MODEL BASED ON SOURCE AND NETWORK CHARACTERISTICS Zerman, Emin; Konuk, Baris; NUR YILMAZ, GÖKÇE; Akar, Gözde (2014-10-30) The increasing demand for streaming video raises the need for flexible and easily implemented Video Quality Assessment (VQA) metrics. Although there are different VQA metrics, most of these are either Full-Reference (FR) or Reduced-Reference (RR). Both FR and RR metrics bring challenges for on-the-fly multimedia systems due to the necessity of additional network traffic for reference data. No-eference (NR) video metrics, on the other hand, as the name suggests, are much more flexible for user-end applicatio...
Visual Group Binary Signature for Video Copy Detection Ozkan, Savas; Esen, Ersin; Akar, Gözde (2014-08-28) Need for automatic video copy detection is increased with the recent technical developments in the internet technologies and video recording. Even though image-based techniques with bag-of-word kind of representations are accepted as the best solution because of robustness and speed; they discard the convenient geometric relation which exists among interest points. In this work, we propose a novel geometric relation which computes a binary signature leveraging existence and non-existence of interest points ...
Automatic Semantic Content Extraction in Videos Using a Fuzzy Ontology and Rule-Based Model Yildirim, Yakup; Yazıcı, Adnan; Yilmaz, Turgay (2013-01-01) Recent increase in the use of video-based applications has revealed the need for extracting the content in videos. Raw data and low-level features alone are not sufficient to fulfill the user's needs; that is, a deeper understanding of the content at the semantic level is required. Currently, manual techniques, which are inefficient, subjective and costly in time and limit the querying capabilities, are being used to bridge the gap between low-level representative features and high-level semantic content. H...
Automatic semantic content extraction in videos using a spatio-temporal ontology model Yıldırım, Yakup; Yazıcı, Adnan; Department of Computer Engineering (2009) Recent increase in the use of video in many applications has revealed the need for extracting the content in videos. Raw data and low-level features alone are not sufficient to fulfill the user's need; that is, a deeper understanding of the content at the semantic level is required. Currently, manual techniques are being used to bridge the gap between low-level representative features and high-level semantic content, which are inefficient, subjective and costly in time and have limitations on querying capab...
A SPATIOTEMPORAL NO-REFERENCE VIDEO QUALITY ASSESSMENT MODEL Konuk, Baris; Zerman, Emin; NUR YILMAZ, GÖKÇE; Akar, Gözde (2013-09-18) Many researchers have been developing objective video quality assessment methods due to increasing demand for perceived video quality measurement results by end users to speed-up advancements of multimedia services. However, most of these methods are either Full-Reference (FR) metrics, which require the original video or Reduced-Reference (RR) metrics, which need some features extracted from the original video. No-Reference (NR) metrics, on the other hand, do not require any information about the original v...

Citation Formats

S. Ozkan, E. Esen, and G. Akar, “ENHANCED SPATIO-TEMPORAL VIDEO COPY DETECTION BY COMBINING TRAJECTORY AND SPATIAL CONSISTENCY,” presented at the IEEE International Conference on Image Processing (ICIP), Paris, FRANCE, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52870.