A system for estimating vehicular speed based on monocular video data by encoding spatio-temporal motion features, the system comprising: a camera mounted to a vehicle and configured to capture monocular video data; a memory configured to store data and processor-executable instructions; a processor configured to execute the processor-executable instructions stored in the memory to: receive, from the camera, pre-training video data captured while the vehicle is in motion, duplicate a first channel of the pre-training video data as a second channel of pre-training video data, wherein the first and second channels of pre-training video data are provided to train one or more filters of a synchrony autoencoder, train the one or more filters of the synchrony autoencoder using the pre-training video data to minimize reconstruction error, and pre-train a convolutional neural network by initializing a first layer of the convolutional neural network with the weights of the trained one or more filters from the synchrony autoencoder, following said pre-training of the convolutional neural network, the processor is further configured to receive real-time video data from the camera while the vehicle is in motion, provide a first channel of the real-time video data without a duplicate second channel to the pre-trained convolutional neural network, receive an estimated vehicle movement parameter from the pre-trained convolutional neural network, and output the estimated vehicle movement parameter to at least one of an audio/visual system and a driver assistance system of the vehicle. a camera mounted to a vehicle and configured to capture monocular video data; a memory configured to store data and processor-executable instructions; a processor configured to execute the processor-executable instructions stored in the memory to: receive, from the camera, pre-training video data captured while the vehicle is in motion, duplicate a first channel of the pre-training video data as a second channel of pre-training video data, wherein the first and second channels of pre-training video data are provided to train one or more filters of a synchrony autoencoder, train the one or more filters of the synchrony autoencoder using the pre-training video data to minimize reconstruction error, and pre-train a convolutional neural network by initializing a first layer of the convolutional neural network with the weights of the trained one or more filters from the synchrony autoencoder, following said pre-training of the convolutional neural network, the processor is further configured to receive real-time video data from the camera while the vehicle is in motion, provide a first channel of the real-time video data without a duplicate second channel to the pre-trained convolutional neural network, receive an estimated vehicle movement parameter from the pre-trained convolutional neural network, and output the estimated vehicle movement parameter to at least one of an audio/visual system and a driver assistance system of the vehicle. receive, from the camera, pre-training video data captured while the vehicle is in motion, duplicate a first channel of the pre-training video data as a second channel of pre-training video data, wherein the first and second channels of pre-training video data are provided to train one or more filters of a synchrony autoencoder, train the one or more filters of the synchrony autoencoder using the pre-training video data to minimize reconstruction error, and pre-train a convolutional neural network by initializing a first layer of the convolutional neural network with the weights of the trained one or more filters from the synchrony autoencoder, following said pre-training of the convolutional neural network, the processor is further configured to receive real-time video data from the camera while the vehicle is in motion, provide a first channel of the real-time video data without a duplicate second channel to the pre-trained convolutional neural network, receive an estimated vehicle movement parameter from the pre-trained convolutional neural network, and output the estimated vehicle movement parameter to at least one of an audio/visual system and a driver assistance system of the vehicle. receive real-time video data from the camera while the vehicle is in motion, provide a first channel of the real-time video data without a duplicate second channel to the pre-trained convolutional neural network, receive an estimated vehicle movement parameter from the pre-trained convolutional neural network, and output the estimated vehicle movement parameter to at least one of an audio/visual system and a driver assistance system of the vehicle.