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The smart city is an important direction for the development of the highly information‐based city, and indoor navigation and positioning technology is an important basis for the realization of an intelligent city. In recent years, indoor positioning technology mainly relies on WiFi, radio frequency identification (RFID), Bluetooth, and so on. Yet, the implementation of the above method requires the relevant equipment to be laid out in advance, and it is only suitable for indoor positioning with low accuracy requirements owing to interference and fading of the signal. The visual‐based positioning technology can achieve high‐precision positioning in enclosed, semienclosed, and multiwalled indoor environments with strong electromagnetic interference by means of epipolar geometry and image matching. The visual‐based indoor positioning mostly uses the random sample consensus (RANSAC) algorithm to estimate the …