Xinggang Lin | Tsinghua University (original) (raw)

Papers by Xinggang Lin

Error concealment is becoming increasingly important because of the growing interest in multimedi... more Error concealment is becoming increasingly important because of the growing interest in multimedia transmission over unreliable channels such as wireless channel. At present most concealment method has its own advantage as well as applicable limitation. In different case, it can achieve different concealment effect. In our paper, we present a novel feature-based image error detection and error concealment algorithm to

Image and Video Communications and Processing 2003, 2003

ABSTRACT Error concealment is becoming increasingly important because of the growing interest in ... more ABSTRACT Error concealment is becoming increasingly important because of the growing interest in multimedia transmission over unreliable channels such as wireless channel. At present most concealment method has its own advantage as well as applicable limitation. In different case, it can achieve different concealment effect. In our paper, we present a novel feature-based image error detection and error concealment algorithm to improve the image quality which was degraded during its transmission over wireless channel. First a simulation channel based on Rayleigh mode is implemented to emulating the actual wireless fading channel characterized by fading, multipath and Doppler frequency shift. The damaged image blocks are detected by exploring the contextual information in images, such as their consistency and edge continuity. The statistical characteristics of missing blocks are then estimated based on the types of their surrounding blocks (e.g., smoothness, texture and edge). Finally different error concealment strategies are applied to different types of blocks in order to achieve better visual quality. Instead of assuming random errors in packets, we simulate the errors of wireless channel based on the Rayleigh model. The proposed algorithm is tested on a number of still images. Simulation results demonstrate that our proposed algorithm is effective in terms of visual quality assessment and PSNR.

Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint, 2003

2010 IEEE International Conference on Image Processing, 2010

ABSTRACT Object tracking is a major technique in image processing and computer vision. In this pa... more ABSTRACT Object tracking is a major technique in image processing and computer vision. In this paper, we propose a new robust feature-based tracking scheme by employing adaptive classifiers to match the detected keypoints in consecutive frames. The novelty of this paper is that the design of online boosting is combined with the invariance of local features so that the classifier-based descriptions are formed in association with the scale and rotation information. Furthermore, we introduce a sample weighting mechanism in the on-line classifier updating, for the subsequent tracking. Experimental results demonstrate the robustness and accuracy of our proposed technique.

2013 IEEE International Conference on Image Processing, 2013

ABSTRACT In this paper, we propose a matting algorithm based on iterative transductive learning (... more ABSTRACT In this paper, we propose a matting algorithm based on iterative transductive learning (for short: ITM). To avoid over-smooth results of recent methods, we introduce the influence of unlabeled regions as well as the consistency of neighboring pixels to re-design the optimization for alpha matting. A novel asymmetric Laplacian matrix is also proposed to further relieve the over-smoothness. To optimize the matting problem, we adjust the constrain coefficients between the initialized alpha matte and the asymmetric Laplacian matrix iteratively to achieve accurate alpha mattes. Consequently, during the iteration, high confidence pixels maintain their refined alpha values, whereas low confidence ones are updated by their neighbors gradually. Experimental results demonstrate that our algorithm is more precise than many state-of-the-art methods in terms of the accuracy.

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2000

ABSTRACT To satisfy the rigorous limitation of delay in real time transmission of high quality vi... more ABSTRACT To satisfy the rigorous limitation of delay in real time transmission of high quality video, the coding rate and transmission rate should be selected judiciously. For the ATM variable bit rate (VBR) channel, the channel rate is tightly restrained by the traffic contract negotiated before communication. The leaky-bucket based rate control algorithm proposed by us could meet the delay and traffic contract, so as to abstain the cell loss over the user-network interface (UNI). Furthermore, in order to benefit the statistical multiplexing and improve the overall decoded video quality, the burstiness of the MPEG encoded stream is reduced dramatically in our system. Our experiment shows that the algorithm is a good compromise between CBR (constant bit rate) and VBR video coding. And its implementation is so simple that it could be easily utilized in on-line rate control for real-time video communication

Image and Video Communications and Processing 2003, 2003

Selective enhancement mechanism of Fine-Granular-Scalability (FGS) In MPEG-4 is able to enhance s... more Selective enhancement mechanism of Fine-Granular-Scalability (FGS) In MPEG-4 is able to enhance specific objects under bandwidth variation. A novel technique for self-adaptive enhancement of interested regions based on Motion Vectors (MVs) of the base layer is proposed, which is suitable for those video sequences having still background and what we are interested in is only the moving objects in the scene, such as news broadcasting, video surveillance, Internet education, etc. Motion vectors generated during base layer encoding are obtained and analyzed. A Gaussian model is introduced to describe non-moving macroblocks which may have non-zero MVs caused by random noise or luminance variation. MVs of these macroblocks are set to zero to prevent them from being enhanced. A segmentation algorithm, region growth, based on MV values is exploited to separate foreground from background. Post-process is needed to reduce the influence of burst noise so that only the interested moving regions are left. Applying the result in selective enhancement during enhancement layer encoding can significantly improves the visual quality of interested regions within an aforementioned video transmitted at different bit-rate in our experiments.

Image and Video Communications and Processing 2003, 2003

ABSTRACT This paper proposes a novel robust framework for scalable video over Internet. The main ... more ABSTRACT This paper proposes a novel robust framework for scalable video over Internet. The main contribute of our work is that a simplified rate-distortion theory is specially developed for scalable bit-stream over the network and the corresponding bit allocation is presented to determine the sets of the channel rate for each video layer. Compared with the traditional iterative optimal bit allocation with complexity time, simulations show that our scheme achieves high quality video transmission with much less complexity time, only no more than 0.2dB under different network conditions (different bandwidth and different packet loss case). Besides, our error control scheme can be naturally combined with congestion control and error resilient techniques to enhance the performance of the overall system.

Visual Communications and Image Processing '93, 1993

ABSTRACT Motion estimation and compensation are important tasks in image sequence coding. In this... more ABSTRACT Motion estimation and compensation are important tasks in image sequence coding. In this paper, we present a motion estimation scheme with multiresolution tree structure and hierarchical motion vector search. Experiments and analysis show that this scheme is not only computation efficient, but also robust. The multiresolution tree structure is further utilized in a variable block size image sequence coding scheme that incorporates the visual spatio-temporal characteristics. Both DCT and quadtree approaches are used to encode the motion compensated prediction error. Although the signal-to-noise ratio of the quadtree coded image is a little lower, the subjective quality around sharp edges is much better. Comparing our extensive simulation results with the MPEG-1 standard, we have obtained quite promising results.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Multimedia and Expo, 2007 IEEE International Conference on, 2007

Lecture Notes in Computer Science, 2005

In front-view facial images, chin contour is a relative stable shape feature and can be widely us... more In front-view facial images, chin contour is a relative stable shape feature and can be widely used in face recognition. But it is hard to extract by conventional edge-detection methods due to the complexities of grayscale distribution in chin area. This paper presents an effective approach to chin contour extraction using the facial parts distributing rules and approved snake model. We first approximately localize a parabola as the initial contour according to prior statistical knowledge, then use approved active contour model to find the real chin contour through iteration. Experimental results show that by this algorithm we can extract the precise chin contour which preserves lots of details for face recognition.

18th International Conference on Pattern Recognition (ICPR'06), 2006

Neurocomputing, 2014

ABSTRACT Dog face detection is an important object detection task, widely applied in many fields ... more ABSTRACT Dog face detection is an important object detection task, widely applied in many fields such as auto-focus and image retrieval. In many applications, users only care about specific target species, which are unknown to a detection system until the users register some relevant information like a limited number of target samples. We call this scenario the detection of user-registered dog faces. Due to the great variation between different dog species, no single model can describe all the species well. Meanwhile, it is also impractical to learn individual models for every potential target species that the users may care about, given the large number of dog species. Furthermore, the registered samples are usually too few to train a robust detector directly. In this context, we propose a novel user-registered object detection framework. This framework can generate an adaptive detector, from only a limited number of user-registered target samples and a couple of off-line trained auxiliary models. In addition, we build an annotated dog face dataset, which contains 10,712 images of 32 species. Experimental results on the dataset demonstrate that the proposed framework can achieve superior detection performance to the state-of-the-art approaches.

Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004., 2004

... 19-21,2004 (4| Wiegand T., Sullivan GJ, Bjontegaard G., and Luthra A., Overview of theH.264/A... more ... 19-21,2004 (4| Wiegand T., Sullivan GJ, Bjontegaard G., and Luthra A., Overview of theH.264/AVC video coding standard, IEEE Trans. Circuits Syst. Video Technol., 13 (7), pp. 560-576, July 2003 [5] Joint Video Team (JVT), reference software JM7.3, ftp://frp.imtc-files.org/ ...

Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004., 2004

ABSTRACT With the prevalent handheld device like digital camera, video shot can be easily obtaine... more ABSTRACT With the prevalent handheld device like digital camera, video shot can be easily obtained. However, generally such video has the jitter problem resulted from cameraman's hands shake. In this paper, a framework is proposed to stabilize the jitter videos, including three modules: global motion estimation, motion filter and motion compensation. There are two contributions in this paper. (1) In the global motion estimation, a edge-based method is introduced to deal with the luminance's sudden change between adjacent frames; (2) In the motion filter module, a novel two-order B-Spline motion filter is proposed to alleviate jitter effect. Experimental results show that our method can suppress the video jitter and improve visual effect significantly.

2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2012

2012 19th IEEE International Conference on Image Processing, 2012

ABSTRACT This paper proposes a novel local matting algorithm based on sample-pair propagation and... more ABSTRACT This paper proposes a novel local matting algorithm based on sample-pair propagation and iterative refinement. Since sample-pairs of the foreground and background in the neighborhood are limited, they fail to fit the linear model well. We propose a sample-pair propagation scheme which propagates the confident sample-pair of each pixel to its neighbors so that they can collect more confident sample-pairs to estimate alpha values accurately. To avoid high time and space complexity of the global optimization, we convert matting into a de-noising problem and refine alpha values via fitting the linear model and smoothing the alpha matte locally and iteratively. Experimental results demonstrate that our algorithm produces more accurate results than the state-of-the-art of local matting.

2009 IEEE International Conference on Multimedia and Expo, 2009

2010 IEEE International Conference on Image Processing, 2010

This paper introduces a topology based affine invariant descriptor for maximally stable extremal ... more This paper introduces a topology based affine invariant descriptor for maximally stable extremal regions (MSERs). The popular SIFT descriptor computes the texture information on a grey-scale patch. Instead our descriptor use only the topology and geometric information among MSERs so that features can be rapidly matched regardless of the texture in the image patch. Based on the ellipses fitting for

Error concealment is becoming increasingly important because of the growing interest in multimedi... more Error concealment is becoming increasingly important because of the growing interest in multimedia transmission over unreliable channels such as wireless channel. At present most concealment method has its own advantage as well as applicable limitation. In different case, it can achieve different concealment effect. In our paper, we present a novel feature-based image error detection and error concealment algorithm to

Image and Video Communications and Processing 2003, 2003

ABSTRACT Error concealment is becoming increasingly important because of the growing interest in ... more ABSTRACT Error concealment is becoming increasingly important because of the growing interest in multimedia transmission over unreliable channels such as wireless channel. At present most concealment method has its own advantage as well as applicable limitation. In different case, it can achieve different concealment effect. In our paper, we present a novel feature-based image error detection and error concealment algorithm to improve the image quality which was degraded during its transmission over wireless channel. First a simulation channel based on Rayleigh mode is implemented to emulating the actual wireless fading channel characterized by fading, multipath and Doppler frequency shift. The damaged image blocks are detected by exploring the contextual information in images, such as their consistency and edge continuity. The statistical characteristics of missing blocks are then estimated based on the types of their surrounding blocks (e.g., smoothness, texture and edge). Finally different error concealment strategies are applied to different types of blocks in order to achieve better visual quality. Instead of assuming random errors in packets, we simulate the errors of wireless channel based on the Rayleigh model. The proposed algorithm is tested on a number of still images. Simulation results demonstrate that our proposed algorithm is effective in terms of visual quality assessment and PSNR.

Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint, 2003

2010 IEEE International Conference on Image Processing, 2010

ABSTRACT Object tracking is a major technique in image processing and computer vision. In this pa... more ABSTRACT Object tracking is a major technique in image processing and computer vision. In this paper, we propose a new robust feature-based tracking scheme by employing adaptive classifiers to match the detected keypoints in consecutive frames. The novelty of this paper is that the design of online boosting is combined with the invariance of local features so that the classifier-based descriptions are formed in association with the scale and rotation information. Furthermore, we introduce a sample weighting mechanism in the on-line classifier updating, for the subsequent tracking. Experimental results demonstrate the robustness and accuracy of our proposed technique.

2013 IEEE International Conference on Image Processing, 2013

ABSTRACT In this paper, we propose a matting algorithm based on iterative transductive learning (... more ABSTRACT In this paper, we propose a matting algorithm based on iterative transductive learning (for short: ITM). To avoid over-smooth results of recent methods, we introduce the influence of unlabeled regions as well as the consistency of neighboring pixels to re-design the optimization for alpha matting. A novel asymmetric Laplacian matrix is also proposed to further relieve the over-smoothness. To optimize the matting problem, we adjust the constrain coefficients between the initialized alpha matte and the asymmetric Laplacian matrix iteratively to achieve accurate alpha mattes. Consequently, during the iteration, high confidence pixels maintain their refined alpha values, whereas low confidence ones are updated by their neighbors gradually. Experimental results demonstrate that our algorithm is more precise than many state-of-the-art methods in terms of the accuracy.

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2000

ABSTRACT To satisfy the rigorous limitation of delay in real time transmission of high quality vi... more ABSTRACT To satisfy the rigorous limitation of delay in real time transmission of high quality video, the coding rate and transmission rate should be selected judiciously. For the ATM variable bit rate (VBR) channel, the channel rate is tightly restrained by the traffic contract negotiated before communication. The leaky-bucket based rate control algorithm proposed by us could meet the delay and traffic contract, so as to abstain the cell loss over the user-network interface (UNI). Furthermore, in order to benefit the statistical multiplexing and improve the overall decoded video quality, the burstiness of the MPEG encoded stream is reduced dramatically in our system. Our experiment shows that the algorithm is a good compromise between CBR (constant bit rate) and VBR video coding. And its implementation is so simple that it could be easily utilized in on-line rate control for real-time video communication

Image and Video Communications and Processing 2003, 2003

Selective enhancement mechanism of Fine-Granular-Scalability (FGS) In MPEG-4 is able to enhance s... more Selective enhancement mechanism of Fine-Granular-Scalability (FGS) In MPEG-4 is able to enhance specific objects under bandwidth variation. A novel technique for self-adaptive enhancement of interested regions based on Motion Vectors (MVs) of the base layer is proposed, which is suitable for those video sequences having still background and what we are interested in is only the moving objects in the scene, such as news broadcasting, video surveillance, Internet education, etc. Motion vectors generated during base layer encoding are obtained and analyzed. A Gaussian model is introduced to describe non-moving macroblocks which may have non-zero MVs caused by random noise or luminance variation. MVs of these macroblocks are set to zero to prevent them from being enhanced. A segmentation algorithm, region growth, based on MV values is exploited to separate foreground from background. Post-process is needed to reduce the influence of burst noise so that only the interested moving regions are left. Applying the result in selective enhancement during enhancement layer encoding can significantly improves the visual quality of interested regions within an aforementioned video transmitted at different bit-rate in our experiments.

Image and Video Communications and Processing 2003, 2003

ABSTRACT This paper proposes a novel robust framework for scalable video over Internet. The main ... more ABSTRACT This paper proposes a novel robust framework for scalable video over Internet. The main contribute of our work is that a simplified rate-distortion theory is specially developed for scalable bit-stream over the network and the corresponding bit allocation is presented to determine the sets of the channel rate for each video layer. Compared with the traditional iterative optimal bit allocation with complexity time, simulations show that our scheme achieves high quality video transmission with much less complexity time, only no more than 0.2dB under different network conditions (different bandwidth and different packet loss case). Besides, our error control scheme can be naturally combined with congestion control and error resilient techniques to enhance the performance of the overall system.

Visual Communications and Image Processing '93, 1993

ABSTRACT Motion estimation and compensation are important tasks in image sequence coding. In this... more ABSTRACT Motion estimation and compensation are important tasks in image sequence coding. In this paper, we present a motion estimation scheme with multiresolution tree structure and hierarchical motion vector search. Experiments and analysis show that this scheme is not only computation efficient, but also robust. The multiresolution tree structure is further utilized in a variable block size image sequence coding scheme that incorporates the visual spatio-temporal characteristics. Both DCT and quadtree approaches are used to encode the motion compensated prediction error. Although the signal-to-noise ratio of the quadtree coded image is a little lower, the subjective quality around sharp edges is much better. Comparing our extensive simulation results with the MPEG-1 standard, we have obtained quite promising results.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Multimedia and Expo, 2007 IEEE International Conference on, 2007

Lecture Notes in Computer Science, 2005

In front-view facial images, chin contour is a relative stable shape feature and can be widely us... more In front-view facial images, chin contour is a relative stable shape feature and can be widely used in face recognition. But it is hard to extract by conventional edge-detection methods due to the complexities of grayscale distribution in chin area. This paper presents an effective approach to chin contour extraction using the facial parts distributing rules and approved snake model. We first approximately localize a parabola as the initial contour according to prior statistical knowledge, then use approved active contour model to find the real chin contour through iteration. Experimental results show that by this algorithm we can extract the precise chin contour which preserves lots of details for face recognition.

18th International Conference on Pattern Recognition (ICPR'06), 2006

Neurocomputing, 2014

ABSTRACT Dog face detection is an important object detection task, widely applied in many fields ... more ABSTRACT Dog face detection is an important object detection task, widely applied in many fields such as auto-focus and image retrieval. In many applications, users only care about specific target species, which are unknown to a detection system until the users register some relevant information like a limited number of target samples. We call this scenario the detection of user-registered dog faces. Due to the great variation between different dog species, no single model can describe all the species well. Meanwhile, it is also impractical to learn individual models for every potential target species that the users may care about, given the large number of dog species. Furthermore, the registered samples are usually too few to train a robust detector directly. In this context, we propose a novel user-registered object detection framework. This framework can generate an adaptive detector, from only a limited number of user-registered target samples and a couple of off-line trained auxiliary models. In addition, we build an annotated dog face dataset, which contains 10,712 images of 32 species. Experimental results on the dataset demonstrate that the proposed framework can achieve superior detection performance to the state-of-the-art approaches.

Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004., 2004

... 19-21,2004 (4| Wiegand T., Sullivan GJ, Bjontegaard G., and Luthra A., Overview of theH.264/A... more ... 19-21,2004 (4| Wiegand T., Sullivan GJ, Bjontegaard G., and Luthra A., Overview of theH.264/AVC video coding standard, IEEE Trans. Circuits Syst. Video Technol., 13 (7), pp. 560-576, July 2003 [5] Joint Video Team (JVT), reference software JM7.3, ftp://frp.imtc-files.org/ ...

Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004., 2004

ABSTRACT With the prevalent handheld device like digital camera, video shot can be easily obtaine... more ABSTRACT With the prevalent handheld device like digital camera, video shot can be easily obtained. However, generally such video has the jitter problem resulted from cameraman's hands shake. In this paper, a framework is proposed to stabilize the jitter videos, including three modules: global motion estimation, motion filter and motion compensation. There are two contributions in this paper. (1) In the global motion estimation, a edge-based method is introduced to deal with the luminance's sudden change between adjacent frames; (2) In the motion filter module, a novel two-order B-Spline motion filter is proposed to alleviate jitter effect. Experimental results show that our method can suppress the video jitter and improve visual effect significantly.

2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2012

2012 19th IEEE International Conference on Image Processing, 2012

ABSTRACT This paper proposes a novel local matting algorithm based on sample-pair propagation and... more ABSTRACT This paper proposes a novel local matting algorithm based on sample-pair propagation and iterative refinement. Since sample-pairs of the foreground and background in the neighborhood are limited, they fail to fit the linear model well. We propose a sample-pair propagation scheme which propagates the confident sample-pair of each pixel to its neighbors so that they can collect more confident sample-pairs to estimate alpha values accurately. To avoid high time and space complexity of the global optimization, we convert matting into a de-noising problem and refine alpha values via fitting the linear model and smoothing the alpha matte locally and iteratively. Experimental results demonstrate that our algorithm produces more accurate results than the state-of-the-art of local matting.

2009 IEEE International Conference on Multimedia and Expo, 2009

2010 IEEE International Conference on Image Processing, 2010

This paper introduces a topology based affine invariant descriptor for maximally stable extremal ... more This paper introduces a topology based affine invariant descriptor for maximally stable extremal regions (MSERs). The popular SIFT descriptor computes the texture information on a grey-scale patch. Instead our descriptor use only the topology and geometric information among MSERs so that features can be rapidly matched regardless of the texture in the image patch. Based on the ellipses fitting for