• Title/Summary/Keyword: Scene Matching

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View synthesis in uncalibrated images (임의 카메라 구조에서의 영상 합성)

  • Kang, Ji-Hyun;Kim, Dong-Hyun;Sohn, Kwang-Hoon
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.437-438
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    • 2006
  • Virtual view synthesis is essential for 3DTV systems, which utilizes the motion parallax cue. In this paper, we propose a multi-step view synthesis algorithm to efficiently reconstruct an arbitrary view from limited number of known views of a 3D scene. We describe an efficient image rectification procedure which guarantees that an interpolation process produce valid views. This rectification method can deal with all possible camera motions. The idea consists of using a polar parameterization of the image around the epipole. Then, to generate intermediate views, we use an efficient dense disparity estimation algorithm considering features of stereo image pairs. Main concepts of the algorithm are based on the region dividing bidirectional pixel matching. The estimated disparities are used to synthesize intermediate view of stereo images. We use computer simulation to show the result of the proposed algorithm.

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3-D Object Recognition Using Surface Normal Images (면 법선 영상을 이용한 3차원 물체 인식)

  • 박종훈;장태규;최종수
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.28B no.9
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    • pp.727-738
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    • 1991
  • This paper presents a new approach to explicityly use surface normal images (SNIs) in 3-D object model description and recognition procedure. The surface normal images of an object are defined as the projected images obtained from view angles facing normal to each surface of the object. The proposed approach can significantly alleviate the difficulty of obtaining correspondence between models and scene objects by explicitly providing a transform for the matching. The proposed approach is applied to the construction of a model-based 3-D object recognition system for the selected five objects. Synthetic images are used in the experiment to show the operation of the overall recognition system.

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A Study on the Depth Map using Single Edge (단일 엣지를 이용한 깊이 정보에 관한 연구)

  • Kim, Young-Seop;Song, Eung-Yeol
    • Journal of the Semiconductor & Display Technology
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    • v.9 no.2
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    • pp.123-126
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    • 2010
  • An implementation of modified stereo matching using efficient belief propagation (BP) algorithm is presented in this paper. We do recommend the use of the simple sobel, prewitt edge operator. The application of B band sobel edge operator over image demonstrates result with somewhat noisy (distinct border). When we adopt the only MRF + BP algorithm, however, borders cannot be distinguished due to that the message functions in the BP algorithm is just the mechanism which passes energy data to the only large gap of each Message functions In order to address the abovementioned disadvantageous phenomenon, we use the sobel edge operator + MRF + BP algorithm to distinguish the border that is located between the similar message data. Using edge information, the result shows that our proposed process diminishes the propagation of wrong probabilistic information. The enhanced result is due to that our proposed method effectively reduced errors incurred by ambiguous scene properties.

Realistic Soap Bubble Appearance using Background Scene and Kelvin Temperature Matching

  • Yoo, Sangwook;Chin, Seongah
    • International Journal of Advanced Culture Technology
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    • v.9 no.3
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    • pp.265-270
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    • 2021
  • VR and AR contents provide a rich user experience [1]. Realistic content with human computer interaction and immersion provides an improved user experience, but there is a limit to producing all elements realistically. In this study, we propose a method to advance the rendering of immersive content using background color information [2]. First, the elements necessary for Kelvin temperature rendering are derived from the color and background as context elements, and the rendering effect has been realized in the soap bubble. For soap bubbles Kelvin temperature rendering, the average color of the background is extracted and the color with the highest similarity is applied by comparing the main color and Kelvin temperature.

Semantic Visual Place Recognition in Dynamic Urban Environment (동적 도시 환경에서 의미론적 시각적 장소 인식)

  • Arshad, Saba;Kim, Gon-Woo
    • The Journal of Korea Robotics Society
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    • v.17 no.3
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    • pp.334-338
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    • 2022
  • In visual simultaneous localization and mapping (vSLAM), the correct recognition of a place benefits in relocalization and improved map accuracy. However, its performance is significantly affected by the environmental conditions such as variation in light, viewpoints, seasons, and presence of dynamic objects. This research addresses the problem of feature occlusion caused by interference of dynamic objects leading to the poor performance of visual place recognition algorithm. To overcome the aforementioned problem, this research analyzes the role of scene semantics in correct detection of a place in challenging environments and presents a semantics aided visual place recognition method. Semantics being invariant to viewpoint changes and dynamic environment can improve the overall performance of the place matching method. The proposed method is evaluated on the two benchmark datasets with dynamic environment and seasonal changes. Experimental results show the improved performance of the visual place recognition method for vSLAM.

Transformer-based dense 3D reconstruction from RGB images (RGB 이미지에서 트랜스포머 기반 고밀도 3D 재구성)

  • Xu, Jiajia;Gao, Rui;Wen, Mingyun;Cho, Kyungeun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.646-647
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    • 2022
  • Multiview stereo (MVS) 3D reconstruction of a scene from images is a fundamental computer vision problem that has been thoroughly researched in recent times. Traditionally, MVS approaches create dense correspondences by constructing regularizations and hand-crafted similarity metrics. Although these techniques have achieved excellent results in the best Lambertian conditions, traditional MVS algorithms still contain a lot of artifacts. Therefore, in this study, we suggest using a transformer network to accelerate the MVS reconstruction. The network is based on a transformer model and can extract dense features with 3D consistency and global context, which are necessary to provide accurate matching for MVS.

Emotion and Sentiment Analysis from a Film Script: A Case Study (영화 대본에서 감정 및 정서 분석: 사례 연구)

  • Yu, Hye-Yeon;Kim, Moon-Hyun;Bae, Byung-Chull
    • Journal of Digital Contents Society
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    • v.18 no.8
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    • pp.1537-1542
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    • 2017
  • Emotion plays a key role in both generating and understanding narrative. In this article we analyzed the emotions represented in a movie script based on 8 emotion types from the wheel of emotions by Plutchik. First we conducted manual emotion tagging scene by scene. The most dominant emotions by manual tagging were anger, fear, and surprise. It makes sense when the film script we analyzed is a thriller-genre. We assumed that the emotions around the climax of the story would be heightened as the tension grew up. From manual tagging we could identify three such duration when the tension is high. Next we analyzed the emotions in the same script using Python-based NLTK VADERSentiment tool. The result showed that the emotions of anger and fear were most matched. The emotion of surprise, anticipation, and disgust, however, scored lower matching.

Autonomous Driving Platform using Hybrid Camera System (복합형 카메라 시스템을 이용한 자율주행 차량 플랫폼)

  • Eun-Kyung Lee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.6
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    • pp.1307-1312
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    • 2023
  • In this paper, we propose a hybrid camera system that combines cameras with different focal lengths and LiDAR (Light Detection and Ranging) sensors to address the core components of autonomous driving perception technology, which include object recognition and distance measurement. We extract objects within the scene and generate precise location and distance information for these objects using the proposed hybrid camera system. Initially, we employ the YOLO7 algorithm, widely utilized in the field of autonomous driving due to its advantages of fast computation, high accuracy, and real-time processing, for object recognition within the scene. Subsequently, we use multi-focal cameras to create depth maps to generate object positions and distance information. To enhance distance accuracy, we integrate the 3D distance information obtained from LiDAR sensors with the generated depth maps. In this paper, we introduce not only an autonomous vehicle platform capable of more accurately perceiving its surroundings during operation based on the proposed hybrid camera system, but also provide precise 3D spatial location and distance information. We anticipate that this will improve the safety and efficiency of autonomous vehicles.

The Recognition of Occluded 2-D Objects Using the String Matching and Hash Retrieval Algorithm (스트링 매칭과 해시 검색을 이용한 겹쳐진 이차원 물체의 인식)

  • Kim, Kwan-Dong;Lee, Ji-Yong;Lee, Byeong-Gon;Ahn, Jae-Hyeong
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.7
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    • pp.1923-1932
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    • 1998
  • This paper deals with a 2-D objects recognition algorithm. And in this paper, we present an algorithm which can reduce the computation time in model retrieval by means of hashing technique instead of using the binary~tree method. In this paper, we treat an object boundary as a string of structural units and use an attributed string matching algorithm to compute similarity measure between two strings. We select from the privileged strings a privileged string wIth mmimal eccentricity. This privileged string is treated as the reference string. And thell we wllstructed hash table using the distance between privileged string and the reference string as a key value. Once the database of all model strings is built, the recognition proceeds by segmenting the scene into a polygonal approximation. The distance between privileged string extracted from the scene and the reference string is used for model hypothesis rerieval from the table. As a result of the computer simulation, the proposed method can recognize objects only computing, the distance 2-3tiems, while previous method should compute the distance 8-10 times for model retrieval.

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Projective Reconstruction Method for 3D modeling from Un-calibrated Image Sequence (비교정 영상 시퀀스로부터 3차원 모델링을 위한 프로젝티브 재구성 방법)

  • Hong Hyun-Ki;Jung Yoon-Yong;Hwang Yong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.2 s.302
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    • pp.113-120
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    • 2005
  • 3D reconstruction of a scene structure from un-calibrated image sequences has been long one of the central problems in computer vision. For 3D reconstruction in Euclidean space, projective reconstruction, which is classified into the merging method and the factorization, is needed as a preceding step. By calculating all camera projection matrices and structures at the same time, the factorization method suffers less from dia and error accumulation than the merging. However, the factorization is hard to analyze precisely long sequences because it is based on the assumption that all correspondences must remain in all views from the first frame to the last. This paper presents a new projective reconstruction method for recovery of 3D structure over long sequences. We break a full sequence into sub-sequences based on a quantitative measure considering the number of matching points between frames, the homography error, and the distribution of matching points on the frame. All of the projective reconstructions of sub-sequences are registered into the same coordinate frame for a complete description of the scene. no experimental results showed that the proposed method can recover more precise 3D structure than the merging method.