1. A machine-implemented method for managing digital videos, comprising: extracting a feature of an input digital video; searching a plurality of candidate features of a plurality of digital ideos for candidate features having similarity to the extracted feature; comparing the extracted feature with each of the candidate features to recognize a matching digital video of the plurality of digital videos having at least one of the candidate features similar to the extracted feature and provide information on the matching digital video corresponding to the at least one similar candidate feature; and wherein extracting the feature of an input digital video includes: decoding the input digital video to generate digital video frames; normalizing the digital video frames to a predetermined uniform size; and extracting temporal and spatial attributes from the video frames with the normalized size, the temporal and spatial attributes being used as the extracted feature, wherein extracting temporal and spatial attributes includes: storing the normalized frames in a frame buffer by a predetermined frame buffer size; dividing the stored normalized frames into 3D-based cubics with predetermined width, height and length; performing 3D transformation on the divided cubics; and performing linear transformation or non-linear transformation on the transformed cubics to extract the temporal and spatial attributes of the input digital video, wherein the predetermined width is determined by dividing a width of the stored normalized frames by a number of cubics in a horizontal direction, the predetermined height is determined by dividing a height of the stored normalized frames by a number of cubics in a vertical direction, and the predetermined length is equal to the predetermined frame buffer size.
1. A machine-implemented method for managing digital videos, comprising: extracting a feature of an input digital video; searching a plurality of candidate features of a plurality of digital ideos for candidate features having similarity to the extracted feature; comparing the extracted feature with each of the candidate features to recognize a matching digital video of the plurality of digital videos having at least one of the candidate features similar to the extracted feature and provide information on the matching digital video corresponding to the at least one similar candidate feature; and wherein extracting the feature of an input digital video includes: decoding the input digital video to generate digital video frames; normalizing the digital video frames to a predetermined uniform size; and extracting temporal and spatial attributes from the video frames with the normalized size, the temporal and spatial attributes being used as the extracted feature, wherein extracting temporal and spatial attributes includes: storing the normalized frames in a frame buffer by a predetermined frame buffer size; dividing the stored normalized frames into 3D-based cubics with predetermined width, height and length; performing 3D transformation on the divided cubics; and performing linear transformation or non-linear transformation on the transformed cubics to extract the temporal and spatial attributes of the input digital video, wherein the predetermined width is determined by dividing a width of the stored normalized frames by a number of cubics in a horizontal direction, the predetermined height is determined by dividing a height of the stored normalized frames by a number of cubics in a vertical direction, and the predetermined length is equal to the predetermined frame buffer size. 4. The machine-implemented method of claim 1 , wherein the step of extracting temporal attribute includes the steps of: dividing each of the normalized frames into image blocks with a predetermined size; detecting a dominant color from each of the divided image blocks; and detecting an edge from an edge image of each of the divided image blocks.