Patent ID: 7164798

Claim:
A method for learning-based automatic commercial content detection, the method comprising: dividing program data into multiple segments; analyzing the segments to determine visual, audio, and context-based feature sets that differentiate commercial content from non-commercial content; and wherein the context-based features are a function of one or more single-side left and/or right neighborhoods of segments of the multiple segments; and wherein the single-side left and/or right neighborhoods are (2n+1) neighborhoods of a current segment C i , and wherein the method further comprises: calculating each of the (2n+1) neighborhoods as follows: N k = [ N s k , N e k ] = { [ min ⁡ ( e j + α ⁢ ⁢ k , 0 ) , e i ] [ s i , e i ] [ s i , min ⁡ ( s i + α ⁢ ⁢ k , L ) ] ⁢ k < 0 k = 0 k > 0 , wherein N k represents 2n+1, n representing a number of neighborhoods left and/or right of C i , [s i , e i ] denoting start and end frame numbers for C i and start and end times for C i , N k s represents a start frame number for N k , N k e represents an end frame number for N k , L indicating a length of the program data, kεZ,|k|≦n, and α a comprising a time step.