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COMPUTATIONAL RAM IMPLEMENTATION OF AN ADAPTIVE VECTOR QUANTIZATION ALGORITHM FOR VIDEO COMPRESSION

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1995年第3期41卷 738-747页

作者： LE, TM PANCHANATHAN, S Department of Electrical Engineering Visual Computing and Communications Laboratory University of Ottawa

Vector Quantization (VQ) is a promising technique for low-bit rate image and video compression. Recently, adaptive VQ-based video compression algorithms have been reported in the literature. This paper proposes an adaptive codebook replenishment VQ algorithm using index-based motion estimation (AVQ+ME) for low-bit rate video compression. The proposed technique has been implemented on a Computational*RAM (C*RAM) SIMD structure.

关键词： Vector quantization Video compression Bit rate Image coding Image sequences Transform coding Multimedia databases Motion estimation Encoding Laboratories

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Spatio-temporal indexing of vector quantized video sequences

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1997年第5期7卷 728-740页

作者： Idris, FM Panchanathan, S Department of Electrical Engineering Visual Computing and Communications Laboratory University of Ottawa Ottawa ONT Canada

visual (image and video) database systems require efficient indexing to enable fast access to the images in a database, In addition, the large memory capacity and channel bandwidth requirements for the storage and transmission of visual data necessitate the use of compression techniques, Vector quantization (VQ) is an efficient technique for low bit-rate image and video compression, In addition, the low complexity of the decoder makes VQ attractive for low power systems and applications which require fast decoding, In this paper, we present an indexing technique for compressed video using vector quantization. Here, a video sequence is first compressed using VQ. Each frame is represented by a usage map, a set of VQ labels, and a set of motion vectors, The video sequence is partitioned into shots and the various camera operations and motion within each shot are then determined by processing the VQ label maps, Each shot is indexed using a spatio-temporal index, The spatial index refers to the spatial content of the representative frame of a shot, while the temporal index represents the temporal content of the shot, The spatial index is based on the codewords used to compress the representative frame, while the temporal index is based on motion and camera operations within the shot, The proposed indexing technique is executed entirely in the compressed domain. This entails significant savings in computational and storage costs resulting in faster execution.

关键词： data compression motion estimation MPEG vector quantization video processing

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STORAGE AND RETRIEVAL OF COMPRESSED IMAGES

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1995年第3期41卷 937-941页

作者： IDRIS, F PANCHANATHAN, S Visual Computing and Communications Laboratory Department of Electrical Engineering University of Ottawa Ottawa ONT Canada

In this paper, we propose a new technique for the storage and retrieval of compressed images. Here, the images are compressed using vector quantization and the codebook is used to generate a feature vector. This feature vector is used as an index to access the images in the database. This technique combines image compression with image indexing. In addition, it has lower storage and computation requirements compared with other techniques reported in the literature.

关键词： Image storage Image retrieval Image coding Indexing Vector quantization Image databases Spatial databases Histograms Clustering algorithms Iterative algorithms

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MKD-YOLO: Multi-Scale and Knowledge-Distilling YOLO for Efficient PPE Compliance Detection

MKD-YOLO: Multi-Scale and Knowledge-Distilling YOLO for Effi...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Juntao Zan Yang Fang Qilie Liu Uswah Khairuddin Yan Li Kaiwei Sun School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Chongqing China Malaysia-Japan International Institute of Technology University of Technology Malaysia Kuala Lumpur Malaysia Department of Electrical and Computer Engineering Inha University Incheon South Korea Key Laboratory of Data Engineering and Visual Computing Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

YOLO-based models are widely used for personal protective equipment (PPE) compliance detection due to their excellent detection performance and efficiency. However, most YOLO models are not competent for detection tasks in complex industrial scenarios such as remote surveillance and extremely small targets. In addition, there is a lack of effective model lightweighting and knowledge transfer approaches for industrial deployment. To this end, this paper proposes a Multi-scale and Knowledge-Distilling YOLO (MKD-YOLO) based on YOLOv8n for efficient PPE compliance detection. Specifically, in backbone stage, we design an Efficient Multi-Scale Enhanced Convolution (C2f-EMSEC) module and Large Spatial Pyramid Pooling-Fast (LSPPF) module for multi-scale and global-contextual feature learning as well as reducing model complexity. Then, in neck stage, a refined Bidirectional feature Pyramid Network (BPNet) is designated to capture fine-grained details for extremely small object detection. Moreover, we apply channel-wise knowledge distillation to facilitate model lightweighting and domain-specific knowledge transfer learning. Experiments on our proposed dataset and public datasets show that the proposed MKD-YOLO achieves a new state-of-the-art (SOTA) detection performance and efficiency for practical PPE compliance detection tasks. Codes and the dataset are available at https://***/z1Zjt/MKD-YOLO.

关键词： Personal protective equipment YOLO Representation learning Convolution Surveillance Speech enhancement Feature extraction Neck Kernel Knowledge transfer

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Pattern recognition tool to detect reconfigurable patterns in MPEG4 video processing 16

Pattern recognition tool to detect reconfigurable patterns i...

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16th International Parallel and Distributed Processing Symposium, IPDPS 2002

作者： Akoglu, A. Dasu, A. Sudarsanam, A. Srinivasan, M. Panchanathan, S. Visual Computing and Communications Laboratory Arizona State University United States

ISBN: (纸本)0769515738

Current approaches towards building a reconfigurable processor are targeted towards general purpose computing or a limited range of media specific applications and are not specifically tuned for mobile multimedia applications. The increasing demand for mobile multimedia processing with stringent constraints for low power, low chip area and high flexibility at both the encoder and decoder naturally demand the design and development of a dynamically reconfigurable multimedia processor. We have performed a detailed complexity analysis of the MPEG-4 video coding mode which has illustrated the potential for reconfigurable computing. We have recently proposed a methodology for designing a reconfigurable media processor. This involves the design of a parser that identifies data/control flow graphs generated from the input assembly code of an UltraSPARC V-9 architecture;recurring pattern analyzer that uses a clustering based approach to identify specific sequences of operations that can potentially be implemented in hardware;and finally a count of such modules at every level of granularity with the associated weights based on the complexity of computation and data transfers used by partitioner and router. In this paper we then propose the design of the parser and pattern recognizer with results for detecting the reconfigurable patterns in MPEG4. © 2002 IEEE.

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Review of image and video indexing techniques

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JOURNAL OF visual COMMUNICATION AND IMAGE REPRESENTATION 1997年第2期8卷 146-166页

作者： Idris, F Panchanathan, S Visual Computing and Communications Laboratory Department of Electrical Engineering University of Ottawa Ottawa Ontario Canada K1N 6N5

visual database systems require efficient indexing to facilitate fast access to the images and video sequences in the database. Recently, several content-based indexing methods for image and video based on spatial relationships;color, texture, shape, sketch, object motion, and camera parameters have been reported in the literature. The goal of this paper is to provide a critical survey of existing literature on content-based indexing techniques and to point out the relative advantages and disadvantages of each approach. (C) 1997 Academic Press.

关键词： Image analysis

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JPEG based scalable image compression

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COMPUTER communications 1996年第12期19卷 1001-1013页

作者： Panchanathan, S Gamaz, N Jain, A Visual Computing and Communications Laboratory Department of Electrical Engineering University of Ottawa Ottawa Ontario Canada K1N 6N5

In this paper, we present JPEG-based scalable image compression algorithms for storage and transmission applications. The JPEG standard for still image compression provides the framework for reconstructing images in different sizes and picture qualities. These features are generally referred to as spatial and SNR scalability, respectively, and are extremely important in a variety of applications. A review of the different modes of the JPEG standard followed by the implementation and performance evaluation of the progressive and hierarchical coding modes which provide SNR and spatial scalability, respectively, are detailed. We then present a highperformance technique based on Wavelet filter downsampling for achieving spatial scalability within the framework of the hierarchical mode of the JPEG standard. This technique provides substantial improvement in performance while maintaining the compatibility with existing JPEG decoders.

关键词： compression image browsing scalability JPEG wavelet progressive coding hierarchical coding

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A joint compression and indexing technique in wavelet compressed domain

A joint compression and indexing technique in wavelet compre...

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2001 IEEE International Conference on Multimedia and Expo, ICME 2001

作者： Fahmy, G.F. Bhalod, J. Panchanathan, S. Visual Computing and Communications Laboratory Department of Computer Science and Engineering Arizona State University United States

ISBN: (纸本)0769511988

The recent MPEG 4 and JPEG 2000 standards address the need for content based coding and manipulation of visual media. The upcoming MPEG 7 standard proposes content descriptors, which succinctly describe the visual content for the purpose of efficient retrieval. This implies that there is an impending need for efficient and effective joint compression and indexing approaches. Several compressed domain indexing techniques have been presented in the recent literature. These are based on the extraction of features from the compression parameters to derive the indices. However, there is little work in the domain of exploring the use of these features to serve the purposes of both compression and indexing. In this paper, we propose a new technique for joint compression and indexing in the wavelet domain. We note that wavelet based compression is used in JPEG 2000 and (for texture coding) in MPEG 4. In the proposed technique, the wavelet decomposed image is first preprocessed to extract features which are then used for compressing the image as well as for deriving the indices. Extensive simulations have been performed in the JPEG 2000 compressed domain to demonstrate the efficiency of the proposed technique.

关键词： Motion Picture Experts Group standards

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

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Indexing spatial content of still texture in MPEG-4 10

Indexing spatial content of still texture in MPEG-4

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2000 10th European Signal Processing Conference, EUSIPCO 2000

作者： Bhalod, Jayank Zubair, V. Mohammed Panchanathan, S. Visual Computing and Communications Laboratory Department of Computer Science and Engineering Arizona State University TempeAZ United States

ISBN: (纸本)9789521504433

There has been a rapid increase in audio-visual information in digital form with the ever-increasing popularity of the Internet. The Moving Pictures Expert Group has recently presented a video compression and content manipulation standard, called MPEG-4 [1]. This was developed in response to the growing need for a coding method that can facilitate access to visual objects in natural and synthetic moving pictures in a wide variety of applications. In this paper, we propose a method for indexing the spatial content of Still Texture in MPEG-4 Video. There has been a number of approaches proposed recently [1],[3],[5],[6], which address content based indexing using features such as, color, shape and/or texture. We note that the still texture information is encoded using Wavelet Transform in MPEG-4. Since still texture can have an arbitrary shape, we propose to employ a combination of shape, color and texture features. The shape features are derived from the alpha plane and represented using Cubic B-spline approximation. The color and texture features are extracted directly from the wavelet compressed domain. An important attribute of the proposed approach is also the introduction of the novel concept of 'containment' of spatial features for content based indexing. © 2000 EUSIPCO.

关键词： Wavelet transforms

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