수많은 공간지각 연구 결과, Euclidean 3-D 구조는 양안 입체시, 움직임, 입체시와 움직임의 결합, 또는 여러 광학 정보의 결합으로도 복구될 수 없다는 사실이 밝혀졌다. 그러나 인간은 이러한 부정확한 공간지각에도 불구하고 특정 과제를 수행하는 데는 어려움이 전혀 없다. 우리는 인공지능과 컴퓨터 비전에 인간의 기술과 능력을 적용해 왔지만 이러한 기계들은 여전히 인간의 능력보다 훨씬 뒤떨어져 있다. 따라서 우리는 인간이 공간의 깊이를 어떻게 지각하는지, 과제를 수행하기 위해 어떠한 정보들을 사용하여 3차원 공간을 정확하게 지각하는지 이해해야 한다. 이 논문의 목적은 미래에 더욱 발전된 인공지능 로봇에 인간의 능력을 적용하기 위해 공간지각 문헌을 검토하는 것이다.
수많은 공간지각 연구 결과, Euclidean 3-D 구조는 양안 입체시, 움직임, 입체시와 움직임의 결합, 또는 여러 광학 정보의 결합으로도 복구될 수 없다는 사실이 밝혀졌다. 그러나 인간은 이러한 부정확한 공간지각에도 불구하고 특정 과제를 수행하는 데는 어려움이 전혀 없다. 우리는 인공지능과 컴퓨터 비전에 인간의 기술과 능력을 적용해 왔지만 이러한 기계들은 여전히 인간의 능력보다 훨씬 뒤떨어져 있다. 따라서 우리는 인간이 공간의 깊이를 어떻게 지각하는지, 과제를 수행하기 위해 어떠한 정보들을 사용하여 3차원 공간을 정확하게 지각하는지 이해해야 한다. 이 논문의 목적은 미래에 더욱 발전된 인공지능 로봇에 인간의 능력을 적용하기 위해 공간지각 문헌을 검토하는 것이다.
Numerous space perception studies have shown that Euclidean 3-D structure cannot be recovered from binocular stereopsis, motion, combination of stereopsis and motion, or even with combined multiple sources of optical information. Humans, however, have no difficulties to perform the task-specific act...
Numerous space perception studies have shown that Euclidean 3-D structure cannot be recovered from binocular stereopsis, motion, combination of stereopsis and motion, or even with combined multiple sources of optical information. Humans, however, have no difficulties to perform the task-specific action despite of poor shape perception. We have applied humans skill and capabilities to artificial intelligence and computer vision but those machines are still far behind from humans abilities. Thus, we need to understand how we perceive depth in space and what information we use to perceive 3-D structure accurately to perform. The purpose of this paper was to review space perception literatures to apply humans abilities to artificial intelligence robots more advanced in future.
Numerous space perception studies have shown that Euclidean 3-D structure cannot be recovered from binocular stereopsis, motion, combination of stereopsis and motion, or even with combined multiple sources of optical information. Humans, however, have no difficulties to perform the task-specific action despite of poor shape perception. We have applied humans skill and capabilities to artificial intelligence and computer vision but those machines are still far behind from humans abilities. Thus, we need to understand how we perceive depth in space and what information we use to perceive 3-D structure accurately to perform. The purpose of this paper was to review space perception literatures to apply humans abilities to artificial intelligence robots more advanced in future.
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문제 정의
To apply humans’ space perception to robotics including VR and AR system, this review paper provides a historical overview of the shape/space perception literature.
가설 설정
Blank provided an additional experiment to support Luneburg’s mathematical theory[8]. He investigated whether the visual space is hyperbolic or spherical curvature. Two lights were placed closer to an observer and one light was placed farther from the observer so that three lights formed a triangle.
제안 방법
Foley studied locus of perceived equidistance as a function of viewing distance[9]. In his experiment, he used five point-like lights incompleted arkness and varied a viewing distance from the observer. All five lights were placed in the horizontal eye-level plane in front of the observer.
They used a sinusoidal protuberance simulated with a continuous dot surface which directed toward the observer from polar-projected motion. Observers had to judge the height of the protuberance relative to its width at the base by moving the vertical line on the screen to reproduce the height to width ratios. Whereas the observers could not judge the height to width ratios correctly at the small visual angle, they consistently performed correct judgments of the ratio at the large visual angle.
Similarly, the observers’ judgments were systematically distorted with the viewing distance from the observer. The observers overestimated the depth of circular cylinders at a near viewing distance and underestimated at a far viewing distance. In other words, truly circular cylinders appeared elongated at a near distance, close to veridical at an intermediate distance, and flattened at a far distance.
Here, circular cylinders were displayed and the half-heights of their base were varied at three different viewing distances. The task was to judge whether the depth of cylinders was greater than or less than the half-height between 1 (flattened) to 5 (elongated). Similarly, the observers’ judgments were systematically distorted with the viewing distance from the observer.
성능/효과
In conclusion, to understand how humans perceive Euclidean 3-D structure to perform complex visually guided actions accurately is necessary to develop the modern machines, including computer vision, robotics, VR and AR, etc.
The results showed that the judged pointing angles were larger than the veridical pointing angle, 30° at the near distance and smaller at the far distance.
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