2024\u5e7412\u670813\u65e5\u3000\u3000Friday Lunch Seminar\u00a0\uff08\u82f1\u8a9e\u3067\u958b\u50ac\u3057\u307e\u3059\uff09
12:15\u00a0\u301c\u00a013:00
CiNet\u68df\u5927\u4f1a\u8b70\u5ba4\u3068On-line\u3067\u958b\u50ac\u3044\u305f\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u6f14\u984c\uff1aNatural image perception based on statistical image features<\/p>\n\n\n\n

\u60c5\u5831\u901a\u4fe1\u7814\u7a76\u6a5f\u69cb\uff08NICT\uff09
\u672a\u6765ICT\u7814\u7a76\u6240
\u8133\u60c5\u5831\u901a\u4fe1\u878d\u5408\u7814\u7a76\u30bb\u30f3\u30bf\u30fc
\u8133\u60c5\u5831\u901a\u4fe1\u878d\u5408\u7814\u7a76\u5ba4
\u7814\u7a76\u54e1\u3000\u7e54\u9593 \u5927\u6c17<\/p>\n\n\n\n

\u62c5\u5f53PI\uff1a\u756a \u6d69\u5fd7<\/a><\/p>\n\n\n\n

Abstract:
The human visual system can effortlessly perceive rich surface quality and materials of natural surfaces. Psychophysical studies have suggested that such rapid and reliable visual recognition relies on low-level image features, such as the histogram statistics of spatial frequency subbands. In fact, image statistics have been shown to effectively explain texture perception, as they enable us to synthesize images that are indistinguishable from original textures in some cases. On the other hand, textures sharing only image statistics often appear unnatural compared to original images especially when scrutinized, and accurate reproduction of certain surface properties, such as glossiness, has been thought to be particularly challenging. However, recent advances in computational studies have revealed that higher-order image features can better describe human gloss perception and enable more detailed surface representation. In this presentation, I will introduce our studies on the encoding processes of these image features and the mechanisms of texture and material perception, based on analyses of visual evoked potentials. I aim to discuss the validity and limitations of visual recognition based on image features, particularly statistical image features computed across entire images.<\/p>\n\n\n\n

References:
Orima, T*., & Motoyoshi, I. (2021). Analysis and synthesis of natural texture perception from visual evoked potentials. Frontiers in Neuroscience, 876.<\/p>\n\n\n\n

Wakita, S*., Orima, T., & Motoyoshi, I. (2021). Photorealistic reconstruction of visual texture from EEG signals. Frontiers in Computational Neuroscience, 15, 754587.<\/p>\n\n\n\n

Orima, T*., & Motoyoshi, I. (2023). Spatiotemporal cortical dynamics for visual scene processing as revealed by EEG decoding. Frontiers in Neuroscience, 17, 1167719.<\/p>\n\n\n\n

Orima, T*., Wakita, S., & Motoyoshi, I. (2024). Neural basis of perceptual surface qualities and materials: Evidence from EEG decoding. The Journal of Cognitive Neuroscience, in press.<\/p>\n","protected":false},"featured_media":0,"template":"","acf":[],"_links":{"self":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/event\/4619"}],"collection":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/event"}],"about":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/types\/event"}],"version-history":[{"count":0,"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/event\/4619\/revisions"}],"wp:attachment":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/media?parent=4619"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}