THE HONG KONG POLYTECHNIC UNIVERSITY

1. THE HONG KONG POLYTECHNIC UNIVERSITY ACM International Conference on Multimedia Retrieval 2011 香港理工大學 Water Reflection Recognition via Minimizing Reflection Cost Based on Motion Blur Invariant Moments Sheng-hua Zhong1, Yan Liu1, Ling Shao2, Fu-lai Chung1 1Department of Computing, The Hong Kong Polytechnic University, Hong Kong SAR, P. R. China 2Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, United Kingdom 1. Motivation and Formulation 4. Reflection Cost Minimization by Dynamic Programming • The existing of water reflection will greatly influence the image analysis; • Little existing technique has been proposed to address water reflection recognition; • Formulates the water reflection recognition as an imperfect reflection symmetry problem. 2. Limitation of Existing Symmetry Detection Technique Final Slide Window 5. Experimental Results • Classify water reflection images with other nature images; • Detect the reflection axis in water reflection images; • Retrieve out water reflection images with10000 other images. (a) Ineffectiveness of global feature on Fourier domain Table2. Classification accuracy (%) in fivefold cross validation. (b) Ineffectiveness of local features on SIFT descriptors’ matching Figure 1. Limitation of Existing symmetry feature space to water reflection problem 3. Summary of Our Work • Construct a feature space MBIS is invariant to motion blur (a) Reflection axis detection result of our algorithm Motion blur: degradation factor due to the relative motion of the sensor and the scene in finite exposure time (b) Reflection axis detection result based on SIFT descriptors’ matching • Propose an efficient detection algorithm RCM to determine the reflection axis in images with water reflection Figure 2. Performance comparison of reflection axis detection Table3. Precision and recall score (%) of retrieval experiment 4. Feature Space Invariants to Motion Blur Figure 3. AveP and NDCG results of the retrieval experiment