• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.75-80
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• 2008

This paper proposes a method to detect scene change using global decision tree that extract boundary cut that have width of big change that happen by camera brake from difference value of frames. First, calculate frame difference value through regional X2-histogram and normalization, next, calculate distance between difference value using normalization. Shot boundary detection is performed by compare global threshold distance with distance value for two adjacent frames that calculating global threshold distance based on distance between calculated difference value. Global decision tree proposed this paper can detect easily sudden scene change such as motion from object or camera and flashlight.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.846-860
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• 2011

The binaural auditory system of human has ability to differentiate the direction and the distance of the sound sources by using the information which are inter-aural intensity difference(IID), inter-aural time difference(ITD) and/or the spectral shape difference(SSD). These information is generated from the acoustical transfer of a sound source to pinna, the outer ears. We can create a virtual sound system using the information which is called Head related transfer function(HRTF). However the performance of 3D sound is not always satisfactory because of non-individual characteristics of the HRTF. In this paper, we propose the algorithm that uses human's auditory characteristics for accurate perception. To achieve this, excitation energy of HRTF, global masking threshold and loudness are applied to the proposed algorithm. Informal listening test shows that the proposed method improves the sound localization characteristics much better than conventional methods.