Theft-resistant video browsing using filtered versions of compressed sequences

Browsing, when used as a sales tool for video sequences, must balance the needs and wants of the customer and merchant: the merchant must offer the customer a preview to allow the customer to select what he or she wants but the merchant does not want to give away the product without payment from the customers. While key-frame browsing discourages theft by not giving the customer the full clip in advance, it may discourage the purchase of some clips because it is not full motion video. We present a new technique for theft resistant video browsing by using limited content, motion browsing clips. Such clips retain most of the important and essential features and content of the original video. Perceptual studies show that people can recognize important features from heavily-filtered image sequences. We show how such sequences can be easily generated directly from a compressed video sequence, saving both bandwidth and computation time