Keyframe based bi directional 2 D mesh representation for video object tracking and manipulation

Date

1999-10-28

Author

Eren, Pekin Erhan

Metadata

Show full item record

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

Item Usage Stats

177
views

0
downloads

We propose a new bi-directional 2-D mesh representation of video objects, which utilizes multiple keyframes with forward and backward tracking. Experimental results on use of this representation for video object tracking in the presence of self occlusion are presented.

Subject Keywords

Bidirectional control, Tracking, Filtering, Image reconstruction

URI

https://hdl.handle.net/11511/68837

DOI

https://doi.org/10.1109/icip.1999.823042

Collections

Graduate School of Informatics, Conference / Seminar

Suggestions

OpenMETU
Core

Bi-directional 2-D mesh representation for video object rendering, editing and superresolution in the presence of occlusion Eren, Pekin Erhan; Tekalp, AM (2003-05-01) In this paper, we propose a new bi-directional 2-D mesh representation of video objects, which utilizes forward and backward reference frames (keyframes). This framework extends the previous uni-directional mesh representation to enable efficient rendering, editing, and superresolution of video objects in the presence of occlusion by allowing bidirectional texture mapping as in MPEG B-frames. The video object of interest is tracked between two successive keyframes (which can be automatically or interactivel...
Correlation tracking based on wavelet domain information Ipek, HL; Yilmaz, I; Yardimci, YC; Cetin, AE (2003-08-07) Tracking moving objects in video can be carried out by correlating a template containing object pixels with pixels of the current frame. This approach may produce erroneous results under noise. We determine a set of significant pixels on the object by analyzing the wavelet transform of the template and correlate only these pixels with the current frame to determine the next position of the object. These significant pixels are easily trackable features of the image and increase the performance of the tracker.
Robust, object-based high-resolution image reconstruction from low-resolution video Eren, Pekin Erhan; Sezan, MI; Tekalp, AM (1997-10-01) We propose a robust, object-based approach to high-resolution image reconstruction from video using the projections onto convex sets (POCS) framework. The proposed method employs a validity map and/or a segmentation map. The validity map disables projections based on observations with inaccurate motion information for robust reconstruction in the presence of motion estimation errors; while the segmentation map enables object-based processing where more accurate motion models can be utilized to improve the q...
Iterative Photometric Stereo with Shadow and Specular Region Detection for 3D Reconstruction BUYUKATALAY, Soner; BİRGÜL, ÖZLEM; Halıcı, Uğur (2009-04-11) Photometric stereo is a 3D reconstruction algorithm that uses the images of an object with different light conditions and its performance is affected by the shades and specular regions in the images. Especially, the use of Lambert reflectance model results in errors in the reconstructed surface normals. In this study an iterative approach was used to generate masks corresponding to these problematic regions and the surface normals were reconstructed using a Lambert based algorithm that excludes these region...
Streaming Multiscale Deep Equilibrium Models Ertenli, Can Ufuk; Akbaş, Emre; Cinbiş, Ramazan Gökberk (2022-1-01) We present StreamDEQ, a method that infers frame-wise representations on videos with minimal per-frame computation. In contrast to conventional methods where compute time grows at least linearly with the network depth, we aim to update the representations in a continuous manner. For this purpose, we leverage the recently emerging implicit layer models, which infer the representation of an image by solving a fixed-point problem. Our main insight is to leverage the slowly changing nature of videos and use the...

Citation Formats

P. E. Eren, “Keyframe based bi directional 2 D mesh representation for video object tracking and manipulation,” 1999, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/68837.