• Title/Summary/Keyword: Object segmentation

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Small Object Segmentation Based on Visual Saliency in Natural Images

  • Manh, Huynh Trung;Lee, Gueesang
    • Journal of Information Processing Systems
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    • v.9 no.4
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    • pp.592-601
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    • 2013
  • Object segmentation is a challenging task in image processing and computer vision. In this paper, we present a visual attention based segmentation method to segment small sized interesting objects in natural images. Different from the traditional methods, we first search the region of interest by using our novel saliency-based method, which is mainly based on band-pass filtering, to obtain the appropriate frequency. Secondly, we applied the Gaussian Mixture Model (GMM) to locate the object region. By incorporating the visual attention analysis into object segmentation, our proposed approach is able to narrow the search region for object segmentation, so that the accuracy is increased and the computational complexity is reduced. The experimental results indicate that our proposed approach is efficient for object segmentation in natural images, especially for small objects. Our proposed method significantly outperforms traditional GMM based segmentation.

Uncertain Region Based User-Assisted Segmentation Technique for Object-Based Video Editing System (객체기반 비디오 편집 시스템을 위한 불확실 영역기반 사용자 지원 비디오 객체 분할 기법)

  • Yu Hong-Yeon;Hong Sung-Hoon
    • Journal of Korea Multimedia Society
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    • v.9 no.5
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    • pp.529-541
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    • 2006
  • In this paper, we propose a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the selected objects are continuously separated from the un selected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable and efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on this result, we have developed objects based video editing system with several convenient editing functions.

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Video Object Segmentation with Weakly Temporal Information

  • Zhang, Yikun;Yao, Rui;Jiang, Qingnan;Zhang, Changbin;Wang, Shi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1434-1449
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    • 2019
  • Video object segmentation is a significant task in computer vision, but its performance is not very satisfactory. A method of video object segmentation using weakly temporal information is presented in this paper. Motivated by the phenomenon in reality that the motion of the object is a continuous and smooth process and the appearance of the object does not change much between adjacent frames in the video sequences, we use a feed-forward architecture with motion estimation to predict the mask of the current frame. We extend an additional mask channel for the previous frame segmentation result. The mask of the previous frame is treated as the input of the expanded channel after processing, and then we extract the temporal feature of the object and fuse it with other feature maps to generate the final mask. In addition, we introduce multi-mask guidance to improve the stability of the model. Moreover, we enhance segmentation performance by further training with the masks already obtained. Experiments show that our method achieves competitive results on DAVIS-2016 on single object segmentation compared to some state-of-the-art algorithms.

Object segmentation and object-based surveillance video indexing

  • Kim, Jin-Woong;Kim, Mun-Churl;Lee, Kyu-Won;Kim, Jae-Gon;Ahn, Chie-Teuk
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1999.06a
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    • pp.165.1-170
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    • 1999
  • Object segmentation fro natural video scenes has recently become one of very active research to pics due to the object-based video coding standard MPEG-4. Object detection and isolation is also useful for object-based indexing and search of video content, which is a goal of the emerging new standard, MPEG-7. In this paper, an automatic segmentation method of moving objects in image sequence is presented which is applicable to multimedia content authoring for MPEG-4, and two different segmentation approaches suitable for surveillance applications are addressed in raw data domain and compressed bitstream domains. We also propose an object-based video description scheme based on object segmentation for video indexing purposes.

Video object segmentation using a novel object boundary linking (새로운 객체 외곽선 연결 방법을 사용한 비디오 객체 분할)

  • Lee Ho-Suk
    • The KIPS Transactions:PartB
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    • v.13B no.3 s.106
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    • pp.255-274
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    • 2006
  • Moving object boundary is very important for the accurate segmentation of moving object. We extract the moving object boundary from the moving object edge. But the object boundary shows broken boundaries so we develop a novel boundary linking algorithm to link the broken boundaries. The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundaries and searches for other terminating pixels to link in concentric circles clockwise within a search radius in the forward direction. The boundary linking algorithm guarantees the shortest distance linking. We register the background from the image sequence using the stationary background filtering. We construct two object masks, one object mask from the boundary linking and the other object mask from the initial moving object, and use these two complementary object masks to segment the moving objects. The main contribution of the proposed algorithms is the development of the novel object boundary linking algorithm for the accurate segmentation. We achieve the accurate segmentation of moving object, the segmentation of multiple moving objects, the segmentation of the object which has a hole within the object, the segmentation of thin objects, and the segmentation of moving objects in the complex background using the novel object boundary linking and the background automatically. We experiment the algorithms using standard MPEG-4 test video sequences and real video sequences of indoor and outdoor environments. The proposed algorithms are efficient and can process 70.20 QCIF frames per second and 19.7 CIF frames per second on the average on a Pentium-IV 3.4GHz personal computer for real-time object-based processing.

Effective segmentation of non-rigid object in a still picture and video sequences (정지영상/동영상에서 non-rigid object의 효율적인 영역 분할 방식에 관한 연구)

  • Lee, In-Jae;Kim, Yong-Ho;Kim, Jung-Gyu;Lee, Myeong-Ho;An, Chi-Deuk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.1
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    • pp.17-31
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    • 2002
  • The new MPEG-4 video coding standard enables content-based functionalities. Image segmentation is an indispensable process for it. This paper addresses an effective segmentation of non-rigid objects. Non-rigid objects are deformable objects with fuzzy, blurred and indefinite boundaries. So it is difficult to segment deformable objects precisely. In order to solve this problem, we propose an effective segmentation of non-rigid objects using watershed algorithms in still pictures. And we propose an automatic segmentation through intra-frame and inter-frame segmentation process in video sequences. Automatic segmentation preforms boundary-based and region-based segmentation to extract precise object boundaries.

Object Segmentation Using ESRGAN and Semantic Soft Segmentation (ESRGAN과 Semantic Soft Segmentation을 이용한 객체 분할)

  • Dongsik Yoon;Noyoon Kwak
    • Journal of Internet of Things and Convergence
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    • v.9 no.1
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    • pp.97-104
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    • 2023
  • This paper is related to object segmentation using ESRGAN(Enhanced Super Resolution GAN) and SSS(Semantic Soft Segmentation). The segmentation performance of the object segmentation method using Mask R-CNN and SSS proposed by the research team in this paper is generally good, but the segmentation performance is poor when the size of the objects is relatively small. This paper is to solve these problems. The proposed method aims to improve segmentation performance of small objects by performing super-resolution through ESRGAN and then performing SSS when the size of an object detected through Mask R-CNN is below a certain threshold. According to the proposed method, it was confirmed that the segmentation characteristics of small-sized objects can be improved more effectively than the previous method.

Image segmentation preserving semantic object contours by classified region merging (분류된 영역 병합에 의한 객체 원형을 보존하는 영상 분할)

  • 박현상;나종범
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.661-664
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    • 1998
  • Since the region segmentation at high resolution contains most of viable semantic object contours in an image, the bottom-up approach for image segmentation is appropriate for the application such as MPEG-4 which needs to preserve semantic object contours. However, the conventioal region merging methods, that follow the region segmentation, have poor performance in keeping low-contrast semantic object contours. In this paper, we propose an image segmentation algorithm based on classified region merging. The algorithm pre-segments an image with a large number of small regions, and also classifies it into several classes having similar gradient characteristics. Then regions only in the same class are merged according to the boundary weakness or statisticsal similarity. The simulation result shows that the proposed image segmentation preserves semantic object contours very well even with a small number of regions.

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Implementation of Video Object Segmentation System for Interactive Personal Broadcasting Service (양방향 개인방송 서비스를 위한 동영상 객체분할 시스템의 구현)

  • Yu, Hong-Yeon;Jun, Do-Young;Kim, Min-Sung;Hong, Sung-Hoon
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.17-19
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    • 2007
  • This paper describe an interactive video object segmentation tool which can be used to generate MPEG-4 video object planes for multimedia broadcasting and enables content based functionalities. In order to apply these functionalities, each frame of video sequence should be represented in terms of video objects. Semiautomatic segmentation can be thought of as a user-assisted segmentation technique. A user can initially mark objects of interest around the real object boundaries. Then the user-guided and selected objects are continuously separated from the unselected areas though time evolution in the image sequences. We proposed method shows very promising result and this encourages the development of object based video editing system.

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Automatic Object Segmentation and Background Composition for Interactive Video Communications over Mobile Phones

  • Kim, Daehee;Oh, Jahwan;Jeon, Jieun;Lee, Junghyun
    • IEIE Transactions on Smart Processing and Computing
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    • v.1 no.3
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    • pp.125-132
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    • 2012
  • This paper proposes an automatic object segmentation and background composition method for video communication over consumer mobile phones. The object regions were extracted based on the motion and color variance of the first two frames. To combine the motion and variance information, the Euclidean distance between the motion boundary pixel and the neighboring color variance edge pixels was calculated, and the nearest edge pixel was labeled to the object boundary. The labeling results were refined using the morphology for a more accurate and natural-looking boundary. The grow-cut segmentation algorithm begins in the expanded label map, where the inner and outer boundary belongs to the foreground and background, respectively. The segmented object region and a new background image stored a priori in the mobile phone was then composed. In the background composition process, the background motion was measured using the optical-flow, and the final result was synthesized by accurately locating the object region according to the motion information. This study can be considered an extended, improved version of the existing background composition algorithm by considering motion information in a video. The proposed segmentation algorithm reduces the computational complexity significantly by choosing the minimum resolution at each segmentation step. The experimental results showed that the proposed algorithm can generate a fast, accurate and natural-looking background composition.

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