A Fast Multi-Banner Counting System using Color and SURF Key-Point Features Classification

• Main Authors: Chia-Ju Lin, 林家儒
• Other Authors: Chueh-Wei Chang
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/5w4m52

碩士 === 國立臺北科技大學 === 資訊工程系研究所 === 100 === In 2012, behind the home base in Los Angeles’ Dodger Stadium, once again there will be the billboard of Taiwan’s Tourism Bureau. The Tourism Bureau has indicated that this year they have prepared a budget of 10 million NT dollar and signed a one year contract with the Dodger Stadium to utilize their billboards to promote Taiwan Tourism. As these advertising billboards are visible to a worldwide audience via television broadcast, regardless of the item being promoted, increased awareness will be achieved by taking advantage of high rating broadcasted locations. The main focus of this paper is of color and SURF. The representative features are identified through filtering by color and recognition of SURF characteristics as well as the distribution of space and information. This helps creating a new index structure with the main features specified, and allowing efficient multiple high-dimensional feature search whilst targeting the basis of visual imagery advertising through sports game broadcasting’s billboard recognition system. The processed features allow each advertising image to maintain its uniqueness and mutually exclusive characteristics. In collaboration of detecting the frame differences, calculating frequency can be markedly decreased. Identification is made by comparison of the similarity of the feature points using sign of the laplacian, distance of the characteristic vectors and the main direction of the synthetic vector. According to the test results, search is accelerated by using the identified main features as it also decreased the number of comparisons required, which in effect achieves more accurate results.