A modified model for the Lobula Giant Movement Detector and its FPGA implementation
Computer Vision and Image Understanding
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A system for the detection of independently moving objects by a moving observer by means of investigating optical flow fields is presented. The usability of the algorithm is shown by a collision detection application. Since the measurement of optical flow is a computationally expensive operation, it is necessary to restrict the number of flow measurements. The first part of the paper describes the usage of a particle filter for the determination of positions where optical flow is calculated. This approach results in a fixed number of optical flow calculations leading to a robust real time detection of independently moving objects on standard consumer PCs. The detection method for independent motion relies on knowledge about the camera motion. Even though inertial sensors provide information about the camera motion, the sensor data does not always satisfy the requirements of the proposed detection method. The second part of this paper therefore deals with the enhancement of the camera motion using image information. The third part of this work specifies the final decision module of the algorithm. It derives a decision (whether to issue a warning or not) from the sparse detection information.