1. A method for detecting a presence of an object in an image, the method comprising: receiving multiple training image samples; using at least one computing device to determine a set of adaptive features for each training image sample, wherein the determining includes: adapting a set of wavelets to match one-by-one to image structures of the respective training image sample, wherein the adapting is implemented approximately using formula: E = min n i , w i ⁢  I - ∑ i ⁢ w i ⁢ ψ n i  2 where E denotes an energy function, ψ n i denotes a wavelet with a wavelet vector parameter with n i , with n i =(c x , c y , , s x , s y ) T , where c x , c y denote position of the wavelet in x and y axis, s x , s y denote scale of the wavelet in x and y axis, and denotes orientation of the wavelet, w i denotes a weight of the wavelet, and I denotes the training image sample; using at least one computing device to integrate the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; using at least one computing device to determine a general feature based on the adaptive feature pool; and using at least one computing device to examine the image using a classifier determined based on the general feature to detect the presence of the object.