In this paper, we propose a new real-time content filtering framework for live broadcasts in TV terminals. Content filtering in TV terminals is a necessary provision of personalized broadcasting services in that it enables a TV viewer to obtain desired scenes from multiple channel broadcasts. In this paper, a stable and reliable filtering structure and an algorithm for multiple inputs are proposed. Moreover, real-time filtering requirements such as frame sampling rate per channel, number of input channels, and buffer condition are analyzed to achieve real-time processing in terminals with limited computing power. Based on queueing theory, we model the system and resolve the filtering requirements. To verify the proposed system and analysis, a filtering algorithm for soccer videos is applied which is modified for real-time processing. Through analysis of visual features (e.g., dominant color and edge components) and detection of spatial objects (e.g., a score board), it recognizes a temporal pattern between successive video frames and filters desired scenes. Experiments on soccer videos have been performed and the results validate the effectiveness of the proposed approach and system.