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 ...
Next step computes the sum of squared differences (SSD) between the average height and each estimated human height. The first and second steps repeat ni times to obtain the error corrected height. 4. Experimental Results The proposed human height estimation results are shown in this section. The...
¥ Each value is extracted from a univariate model; thus, the sum of individual vegetation type changes does not match with total greenspace percentage change. a The negative values do not indicate a possible reduction of vegetation coverage of that type and replace with others; rather, this ...
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 ...
Fig. 1: Impact of covariates on synaptic properties. aSynaptic traces from two studies67,68recording GABAergic signals from CA1 Axo-axonic to CA1 Pyramidal cells in different species. Differences in intracellular solutions are also indicated. Note large differences in g,τd,and U. Neuronal morph...
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 ...
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 鈥榓dditive correction iteration algorithm鈥which the author has been ...
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 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,...