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

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.


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...
Visual object tracking using semi supervised convolutional filters
Sevindik, Emir Can; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2020-10-15)
Visual object tracking aims to find a single object position in a video frame, when a annotated bounding box is provided in the first frame. Correlation filters have always produced excellent results in terms of accuracy, while enjoying quite low computational complexity. The main property of correlation filter based trackers is to find a filter that can generate high values around the true target object location, whereas relatively low values for the locations away from the object. Recently, deep learn...
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.
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: