7. A system comprising: memory; one or more processors; and one or more modules stored in the memory and executable by the one or more processors, the one or more modules including: an extracting module configured to extract features from video data and determine a first set of feature values based on the extracted features; a classifying module configured to apply a classifier to the first set of feature values to determine a second set of feature values and to use the second set of feature values to determine a probability that the video data belongs to at least one semantic category of a predefined set of semantic categories; a scoring module configured to apply a scoring model, based at least in part on the at least one semantic category, to the first set of feature values and the second set of feature values to determine a plurality of desirability scores for the video data, wherein an individual desirability score indicative of video quality is associated with an individual video frame in the video data; and a segmenting module configured to: identify video frames in the video data that have a desirability score above a predetermined threshold desirability score; analyze the video data to determine, in association with the video frames, changes in camera motion and changes in object motion; and locate, based at least in part on the changes in camera motion and the changes in object motion, boundaries in the video data to produce one or more video segments, wherein: an individual video segment includes at least one video frame that has the desirability score above the predetermined threshold desirability score, and the locating the boundaries in the video data comprises determining that object motion intensity of a first video frame and object motion intensity of a second video frame differ by a predetermined threshold.
7. A system comprising: memory; one or more processors; and one or more modules stored in the memory and executable by the one or more processors, the one or more modules including: an extracting module configured to extract features from video data and determine a first set of feature values based on the extracted features; a classifying module configured to apply a classifier to the first set of feature values to determine a second set of feature values and to use the second set of feature values to determine a probability that the video data belongs to at least one semantic category of a predefined set of semantic categories; a scoring module configured to apply a scoring model, based at least in part on the at least one semantic category, to the first set of feature values and the second set of feature values to determine a plurality of desirability scores for the video data, wherein an individual desirability score indicative of video quality is associated with an individual video frame in the video data; and a segmenting module configured to: identify video frames in the video data that have a desirability score above a predetermined threshold desirability score; analyze the video data to determine, in association with the video frames, changes in camera motion and changes in object motion; and locate, based at least in part on the changes in camera motion and the changes in object motion, boundaries in the video data to produce one or more video segments, wherein: an individual video segment includes at least one video frame that has the desirability score above the predetermined threshold desirability score, and the locating the boundaries in the video data comprises determining that object motion intensity of a first video frame and object motion intensity of a second video frame differ by a predetermined threshold. 9. The system of claim 7 , wherein the one or more modules further include a post-processing module configured to: rank the one or more video segments based at least in part on desirability scores of video frames included in an individual video segment; and create a highlight video based at least in part on the ranking.