부산대학교 도서관

Baby Mentor is a system developed to learn and teach babies through images. Through intuitive observations and studies it is shown that using a visual approach i.e. images, videos is an effective method for teaching babies and young children. So for this purpose we present a system that automatically recognizes and generates automatic real time for objects such as toys, picture cards or flashcards that are commonly used by children. The method begins with detecting and extracting features from image for which Scale Invariant Feature Transform (SIFT) algorithm is used. SIFT is scale, rotation and transformation invariant thereby making it easier to identify objects even if it is rotated or placed in dim light. The bag-of-visual-words model (BOVW) is then used to accumulate, cluster and segregate the features of the image generated by the SIFT algorithm, into their respective classes. This helps in generating vocabulary needed to generate the natural language description. Finally the text generated is spoken out through a speaker or microphone. This will help babies especially those suffering from autism in their learning and communication process by helping them identify and understand common world objects with the help of the text and speech generated. Besides this the entire process would require minimal human assistance thus making it a convenient and easy-to-use application.