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논문 기본 정보

자료유형
학술대회자료
저자정보
Dae Yeol Lee (ETRI) Guilherme O. Pinto (Cornell University) Sheila S. Hemami (Cornell University)
저널정보
한국방송·미디어공학회 한국방송미디어공학회 학술발표대회 논문집 2013년도 한국방송공학회 추계 학술대회
발행연도
2013.11
수록면
165 - 168 (4page)

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초록· 키워드

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Image distortions, such as quantization errors, can have a severe negative impact on the performance of computer vision algorithms, and, more specifically, on object detection algorithms. State-of-the-art implementations of the JPEG-2000 image coder commonly allocate the available bits to minimize the Mean-Squared-Error (MSE) distortion between the original image and the resulting compressed image. However, considering that some state-of-the-art object detection methods use the gradient information as the main image feature, an improved object detection performance is expected for JPEG-2000 image coders that allocate the available bits to minimize the distortions on the gradient content. Accordingly, in this work, the Gradient Mean-Squared-Error (GMSE) based JPEG-2000 coder presents an improved object detection performance over the MSE based JPEG-2000 image coder when the object of interest is located at the same spatial location of the image regions with the strongest gradients and also for high bit-rates. For low bit-rates(e.g. 0.07bpp), the GMSE based JPEG-2000 image coder becomes overly selective in choosing the gradients to preserve, and, as a result, there is a greater chance of mismatch between the spatial locations of the gradients that the coder is trying to preserve and the spatial locations of the objects of interest.

목차

Abstract
1. Introduction
2. Background
3. Experimental Setup
4. Result and Analysis
5. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2014-560-002651834