normalized mutual informationsum of squared differencesnonlinear optimizationThis paper presents a novel visual tracking approach that combines the NMI metric and the traditional SSD metric within a gradient-based optimization frame, which can be used for direct visual odometry and SLAM. We firstly ...
That paper proved that if the sign-preservation requirement is dropped then the solution of the so-called improved normalized squared differences (INSD) two-directional matrix adjustment model is the same as the result of the 'additive correction iteration algorithm' which the author has been using...
The discovery of place cells and grid cells underscored the importance of the hippocampal formation as a key neural substrate for spatial navigation1,2, fueling an intensive investigation of this brain region. Understanding spatial coding requires a model of the information flow in the underlying cell...
To this end, the superwideband is split into several subbands, and MDCT coefficients belonging to each subband are normalized by the subband gain that is obtained by squared sum of each MDCT coefficient. We then estimate normalized MDCT coefficients appropriate for the superwideband in order to ...
into an expression involving only the image sum and sum squared under the feature. The construction of the ta- bles requires approximately operations, which is 5 Normalizing less than the cost of computing the numerator by (4) and considerably less than the required to Examining again the ...
We propose a novel tracking algorithm by minimizing the sum-of-squared differences (SSD) between the normalized image gradients of the template image and the input image from the test image sequence. The proposed tracking algorithm is efficient to implement since it is based on the framework of ...
This paper analyzes the performance of sum of squared differences (SSD), sum of absolute differences (SAD), normalized cross correlation (NCC), zero mean normalized cross correlation (ZNCC) and several other proposed modified expressions of NCC. Experimental results on real images demonstrate that ...
We then consider self-normalization by a function of the sum of squared martingale differences as in de la Pe?a et al. (2004)...doi:10.1007/978-3-540-85636-8_8Victor H. de la PeaTze Leung LaiQi-Man Shao
We then consider self-normalization by a function of the sum of squared martingale differences as in de la Pea et al. (2004). This self-normalization yields a universal upper LIL that is applicable to all adapted sequences. In the case of martingales satisfying certain boundedness assumptions,...
Reference matrixRAS-methodSign flipCentral European Journal of Operations Research - Estimating the elements of a matrix, when only the margins (row and column sums) are known, but a supposedly similar 'reference matrix'...Revesz, TamasInstitute for Economics, Corvinus University of Budapest, ...