• Title/Summary/Keyword: Video matching

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Development of System for Real-Time Object Recognition and Matching using Deep Learning at Simulated Lunar Surface Environment (딥러닝 기반 달 표면 모사 환경 실시간 객체 인식 및 매칭 시스템 개발)

  • Jong-Ho Na;Jun-Ho Gong;Su-Deuk Lee;Hyu-Soung Shin
    • Tunnel and Underground Space
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    • v.33 no.4
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    • pp.281-298
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    • 2023
  • Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

A New Adaptive Window Size-based Three Step Search Scheme (적응형 윈도우 크기 기반 NTSS (New Three-Step Search Algorithm) 알고리즘)

  • Yu Jonghoon;Oh Seoung-Jun;Ahn Chang-bum;Park Ho-Chong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.1 s.307
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    • pp.75-84
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    • 2006
  • With considering center-biased characteristic, NTSS(New Three-Step Search Algorithm) can improve the performance of TSS(Three-Step Search Algorithm) which is one of the most popular fast block matching algorithms(BMA) to search a motion vector in a video sequence. Although NTSS has generally better Quality than TSS for a small motion sequence, it is hard to say that NTSS can provide better quality than TSS for a large motion sequence. It even deteriorates the quality to increase a search window size using NTSS. In order to address this drawback, this paper aims to develop a new adaptive window size-based three step search scheme, called AWTSS, which can improve quality at various window sizes in both the small and the large motion video sequences. In this scheme, the search window size is dynamically changed to improve coding efficiency according to the characteristic of motion vectors. AWTSS can improve the video quality more than 0.5dB in case of large motion with keeping the same quality in case of small motion.

Recovering Corrupted Motion Vectors using Discontinuity Features of an Image (영상의 불연속 특성을 이용한 손상된 움직임 벡터 복원 기법)

  • 손남례;이귀상
    • Journal of KIISE:Information Networking
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    • v.31 no.3
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    • pp.298-304
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    • 2004
  • In transmitting a compressed video bit-stream over Internet, a packet loss causes an error propagation in both spatial and temporal domain, which in turn leads to a severe degradation in image quality. In this paper, a new error concealment algorithm is proposed to repair damaged portions of the video frames in the receiver. Conventional BMA(Boundary Matching Algorithm) assumes that the pixels on the boundary of the missing block and its neighboring blocks are very similar, but has no consideration of edges t)r discontinuity across the boundary. In our approach, the edges are detected across the boundary of the lost or erroneous block. Once the edges are detected and the orientation of each edge is found, only the pixel difference along the expected edges across the boundary is measured instead of calculating differences between all adjacent pixels on the boundary. Therefore, the proposed approach needs very few computations and the experiment shows an improvement of the performance over the conventional BMA in terms of both subjective and objective quality of video sequences.

Depth Estimation and Intermediate View Synthesis for Three-dimensional Video Generation (3차원 영상 생성을 위한 깊이맵 추정 및 중간시점 영상합성 방법)

  • Lee, Sang-Beom;Lee, Cheon;Ho, Yo-Sung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.10B
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    • pp.1070-1075
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    • 2009
  • In this paper, we propose new depth estimation and intermediate view synthesis algorithms for three-dimensional video generation. In order to improve temporal consistency of the depth map sequence, we add a temporal weighting function to the conventional matching function when we compute the matching cost for estimating the depth information. In addition, we propose a boundary noise removal method in the view synthesis operation. after finding boundary noise areas using the depth map, we replace them with corresponding texture information from the other reference image. Experimental results showed that the proposed algorithm improved temporal consistency of the depth sequence and reduced flickering artifacts in the virtual view. It also improved visual quality of the synthesized virtual views by removing the boundary noise.

Detection of View Reversal in a Stereo Video (스테레오 동영상에서의 좌우 영상 바뀜 검출 기법)

  • Son, Ji Deok;Song, Byung Cheol
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.191-198
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    • 2013
  • This paper proposes detection of view reversal in a stereo video using depth map and motion vector information. We obtain a depth map by using a stereo matching and divide the input image into foreground and background. Next, we obtain a motion vector field by using a motion estimation. In general, an occluded region is in background when foreground goes toward the adjacent background or the background goes toward the adjacent foreground. But, we will face with the change of foreground and background because their depths also change when view reversal occurs. Therefore, we can detect the view reversal in stereo videos by using the observation that the foreground goes toward the adjacent background or the background goes toward the adjacent foreground. The experimental results show that the proposed algorithm achieves good detection rate when the background region is sufficiently occluded by the moving foreground.

Matching of Topic Words and Non-Sympathetic Types on YouTube Videos for Predicting Video Preference (영상 선호도 예측을 위한 유튜브 영상에 대한 토픽어와 비공감 유형 매칭)

  • Jung, Jimin;Kim, Seungjin;Lee, Dongyun;Kim, Gyotae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.189-192
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    • 2021
  • YouTube, the world's largest video sharing platform, is loved by many users in that it provides numerous videos and makes it easy to get helpful information. However, the ratio of like/hate for each video varies according to the subject or upload time, even though they are in the same channel; thus, previous studies try to understand the reason by inspecting some numerical statistics such as the ratio and view count. They can help know how each video is preferred, but there is an explicit limitation to identifying the cause of such preference. Therefore, this study aims to determine the reason that affects the preference through matching between topic words extracted from comments in each video and non-sympathetic types defined in advance. Among the top 10 channels in the field of 'pets' and 'cooking', where outliers occur a lot, the top 10 videos (the threshold of pet: 4.000, the threshold of cooking: 0.723) with the highest ratio were selected. 11,110 comments collected totally, and topics were extracted and matched with non-sympathetic types. The experimental results confirmed that it is possible to predict whether the rate of like/hate would be high or which non-sympathetic type would be by analyzing the comments.

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Improved Disparity Map Computation on Stereoscopic Streaming Video with Multi-core Parallel Implementation

  • Kim, Cheong Ghil;Choi, Yong Soo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.2
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    • pp.728-741
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    • 2015
  • Stereo vision has become an important technical issue in the field of 3D imaging, machine vision, robotics, image analysis, and so on. The depth map extraction from stereo video is a key technology of stereoscopic 3D video requiring stereo correspondence algorithms. This is the matching process of the similarity measure for each disparity value, followed by an aggregation and optimization step. Since it requires a lot of computational power, there are significant speed-performance advantages when exploiting parallel processing available on processors. In this situation, multi-core CPU may allow many parallel programming technologies to be realized in users computing devices. This paper proposes parallel implementations for calculating disparity map using a shared memory programming and exploiting the streaming SIMD extension technology. By doing so, we can take advantage both of the hardware and software features of multi-core processor. For the performance evaluation, we implemented a parallel SAD algorithm with OpenMP and SSE2. Their processing speeds are compared with non parallel version on stereoscopic streaming video. The experimental results show that both technologies have a significant effect on the performance and achieve great improvements on processing speed.

Fractal Depth Map Sequence Coding Algorithm with Motion-vector-field-based Motion Estimation

  • Zhu, Shiping;Zhao, Dongyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.1
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    • pp.242-259
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    • 2015
  • Three-dimensional video coding is one of the main challenges restricting the widespread applications of 3D video and free viewpoint video. In this paper, a novel fractal coding algorithm with motion-vector-field-based motion estimation for depth map sequence is proposed. We firstly add pre-search restriction to rule the improper domain blocks out of the matching search process so that the number of blocks involved in the search process can be restricted to a smaller size. Some improvements for motion estimation including initial search point prediction, threshold transition condition and early termination condition are made based on the feature of fractal coding. The motion-vector-field-based adaptive hexagon search algorithm on the basis of center-biased distribution characteristics of depth motion vector is proposed to accelerate the search. Experimental results show that the proposed algorithm can reach optimum levels of quality and save the coding time. The PSNR of synthesized view is increased by 0.56 dB with 36.97% bit rate decrease on average compared with H.264 Full Search. And the depth encoding time is saved by up to 66.47%. Moreover, the proposed fractal depth map sequence codec outperforms the recent alternative codecs by improving the H.264/AVC, especially in much bitrate saving and encoding time reduction.

Surveillance Video Retrieval based on Object Motion Trajectory (물체의 움직임 궤적에 기반한 감시 비디오의 검색)

  • 정영기;이규원;호요성
    • Journal of Broadcast Engineering
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    • v.5 no.1
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    • pp.41-49
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    • 2000
  • In this paper, we propose a new method of indexing and searching based on object-specific features at different semantic levels for video retrieval. A moving trajectory model is used as an indexing key for accessing the individual object in the semantic level. By tracking individual objects with segmented data, we can generate motion trajectories and set model parameters using polynomial curve fitting. The proposed searching scheme supports various types of queries including query by example, query by sketch, and query on weighting parameters for event-based video retrieval. When retrieving the interested video clip, the system returns the best matching event in the similarity order.

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Content-Based Video Retrieval Algorithms using Spatio-Temporal Information about Moving Objects (객체의 시공간적 움직임 정보를 이용한 내용 기반 비디오 검색 알고리즘)

  • Jeong, Jong-Myeon;Moon, Young-Shik
    • Journal of KIISE:Software and Applications
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    • v.29 no.9
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    • pp.631-644
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    • 2002
  • In this paper efficient algorithms for content-based video retrieval using motion information are proposed, including temporal scale-invariant retrieval and temporal scale-absolute retrieval. In temporal scale-invariant video retrieval, the distance transformation is performed on each trail image in database. Then, from a given que교 trail the pixel values along the query trail are added in each distance image to compute the average distance between the trails of query image and database image, since the intensity of each pixel in distance image represents the distance from that pixel to the nearest edge pixel. For temporal scale-absolute retrieval, a new coding scheme referred to as Motion Retrieval Code is proposed. This code is designed to represent object motions in the human visual sense so that the retrieval performance can be improved. The proposed coding scheme can also achieve a fast matching, since the similarity between two motion vectors can be computed by simple bit operations. The efficiencies of the proposed methods are shown by experimental results.