Data level fusion using common symmetry set

1999-04-09
Tari, S
Availability of different imaging modalities requires techniques to process and combine information from different images of the same phenomena. We present a symmetry based approach for combining information from multiple images. Fusion is performed at data level. Actual object boundaries and shape descriptors are recovered directly from raw sensor output(s). Method is applicable to arbitrary number of images in arbitrary dimension.

Suggestions

Relaxed Spatio-Temporal Deep Feature Aggregation for Real-Fake Expression Prediction
Ozkan, Savas; Akar, Gözde (2017-10-29)
Frame-level visual features are generally aggregated in time with the techniques such as LSTM, Fisher Vectors, NetVLAD etc. to produce a robust video-level representation. We here introduce a learnable aggregation technique whose primary objective is to retain short-time temporal structure between frame-level features and their spatial interdependencies in the representation. Also, it can be easily adapted to the cases where there have very scarce training samples. We evaluate the method on a real-fake expr...
Temporal watermarking of digital video
Koz, A; Alatan, Abdullah Aydın (2003-04-11)
A video watermarking method is presented, based on the temporal sensitivity of Human Visual System (HVS). The method exploits the temporal contrast thresholds of HVS to determine the spatio-temporal locations, where the watermark should be embedded, and the maximum strength of watermark, which still gives imperceptible distortion after watermark insertion. The robustness results indicate that the proposed scheme survives video distortions, such as additive Gaussian noise, ITU H.263+ coding at medium bit rat...
Fast and accurate semiautomatic haptic segmentation of brain tumor in 3D MRI images
Latifi-Navid, Masoud; Bilen, Murat; Konukseven, Erhan İlhan; Doğan, Musa; Altun, Adnan (The Scientific and Technological Research Council of Turkey, 2016-01-01)
In this study, a novel virtual reality-based interactive method combined with the application of a graphical processing unit (GPU) is proposed for the semiautomatic segmentation of 3D magnetic resonance imaging (MRI) of the brain. The key point of our approach is to use haptic force feedback guidance for the selection of seed points in a bounded volume with similar intensity and gradient. For the automatic determination of a bounded volume of segmentation in real time, parallel computation on the GPU is use...
Foveated image watermarking
Koz, A; Alatan, Abdullah Aydın (2002-09-25)
The spatial resolution of the human visual system (HVS) decreases rapidly away from the point of fixation (foveation point). By exploiting this fact, we propose a watermarking approach that embeds the watermark energy into the image peripheral according to foveation-based HVS contrast thresholds. Compared to the other HVS-based watermarking methods, the simulation results demonstrate an improvement in the robustness of the proposed approach against image degradations, such as JPEG compression, cropping and ...
Adaptive mean-shift for automated multi object tracking
Beyan, C.; Temizel, Alptekin (2012-01-01)
Mean-shift tracking plays an important role in computer vision applications because of its robustness, ease of implementation and computational efficiency. In this study, a fully automatic multiple-object tracker based on mean-shift algorithm is presented. Foreground is extracted using a mixture of Gaussian followed by shadow and noise removal to initialise the object trackers and also used as a kernel mask to make the system more efficient by decreasing the search area and the number of iterations to conve...
Citation Formats
S. Tari, “Data level fusion using common symmetry set,” 1999, vol. 3719, p. 327, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64067.