Jing-Ying Chang

A Localized Approach to Abandoned Luggage Detection with Foreground-Mask Sampling

In this paper we propose a novel approach to the detection of abandoned luggage in video surveillance. Candidates of abandoned luggage items which may pose potential security threats are first identified and localized by our proposed foreground-mask sampling technique. Our approach can deal with luggage pieces of arbitrary shape and color without the need for prior learning, and it works well under crowded and highly-cluttered situations. This localization of suspicious luggage items in the scene enables us to focus attention and subsequent processing solely on their neighborhoods. The owner of the luggage is then located and tracked to determine whether or not the luggage has been abandoned deliberately. A probability model using the MAP principle is employed to calculate a posteriori confidence score for the luggage-abandonment event, and an alarm will be automatically triggered if the certainty of luggage abandonment is higher than a pre-defined threshold. We show our results on the video datasets provided by the 2007 IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS 2007) and the 2006 IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS 2006).

Efficient Content Analysis Engine for Visual Surveillance Network

In the next-generation visual surveillance systems, content analysis tools will be integrated. In this paper, to accelerate these tools, it is proposed to integrate a hardware content analysis engine into a smart camera system-on-a-chip (SoC). A smart camera SoC hardware architecture with the proposed visual content analysis engine is first presented. This engine consists of dedicated accelerators and a programmable morphology coprocessor. Stream processing design concept, frame-level pipelining, and subword level parallelism are employed together to efficiently utilize the bandwidth of the system bus and achieve high throughput. The implementation results show that, with 168 K logic gates and 40.63 Kb on-chip memory, a processing speed of 30 640 x 480 frames/s can be achieved, while the operations of video object segmentation, object description and tracking, and face detection and scoring are supported.

Effective hardware-oriented technique for the rate control of JPEG2000 encoding

A great deal of computation for JPEG2000 encoding is a redundancy when the compression rate is high. That is because many coded bit-streams will be truncated after the rate control of JPEG2000. In this paper, an effective scheme for JPEG2000 rate control is proposed. Through this scheme, the computation complexity for JPEG2000 entropy coding, that is, EBCOT Tier-1, can be greatly reduced almost without paying any penalty on the image quality, especially at lower bit-rate. Moreover, the proposed method is considered to be suitable for the hardware implementation since the existing techniques for the rate control of JPEG2000 are all software-oriented. By the proposed rate control method, a dedicated hardware of JPEG2000 with high-speed processing and effective rate control ability can be achieved.

Relative Depth Layer Extraction for Monoscopic Video by Use of Multidimensional Filter

This paper presents a relative depth layer extraction system for monoscopic video, using multi-line filters and a layer selection algorithm. Main ideas are to extract multiple linear trajectory signals from videos and to determine their relative depths using the concept of motion parallax. The proposed superficial line model used for detecting slow moving objects provides sufficient taps within few frames to reduce frame buffer, while the closest-hit line model used for detecting fast motion objects provides few enough taps to prevent blurring. To increase the correctness of layer map, three-level layer map co-decision is used to compensate low texture region defect

Human Object Tracking Algorithm with Human Color Structure Descriptor for Video Surveillance Systems

Segmentation, tracking, and description extraction are important operations in smart camera surveillance systems. In this paper, a robust segmentation-and-descriptor based tracking algorithm is proposed. Segmentation is applied first, and description for each connected component is extracted for object classification to generate the video object masks. It can do segmentation, tracking, and description extraction with a single algorithm without redundant computation. In addition, a new descriptor for human objects, human color structure descriptor (HCSD), is also proposed for this algorithm. Experimental results show that the proposed algorithm can provide precise video object masks and trajectories. It is also shown that the proposed descriptor, HCSD, can achieve better performance than scalable color descriptor and color structure descriptor of MPEG-7 for human objects

Priority depth fusion for the 2D to 3D conversion system

For the sake of providing 3D contents for up-coming 3D display devices, a real-time automatic depth fusion 2D-to-3D conversion system is needed on the home multimedia platform. We proposed a priority depth fusion algorithm with a 2D-to-3D conversion system which generates the depth map from most of the commercial video sequences. The results from different kinds of depth reconstruction methods are integrated into one depth map by the proposed priority depth fusion algorithm. Then the depth map and the original 2D image are converted to stereo images for showing on the 3D display devices. In this paper, a 2D-to-3D conversion algorithm set is combined with the proposed depth fusion algorithm to show the improved results. With the converted 3D contents, the needs for 3D display devices will also increase. As long as the two technologies evolve, the 3D-TV era will come as soon as possible.

Architecture and analysis of color structure descriptor for real-time video indexing and retrieval

Color structure descriptor (CSD) provides satisfactory image indexing and retrieval results among other color-based descriptors in MPEG-7. The superiority comes from the consideration of space distribution of pixel colors. In this paper, we proposed the first CSD hardware architecture which can generate CSD description with frame size 256×256 and 30 frames per second (fps). This architecture provides about 12 times speed-up than running on a 2.54 GHz microprocessor platform to achieve real-time applications like assisting rate control in video coding system and circumstance change detection in surveillance system.

Line Buffer Wordlength Analysis for Line-Based 2-D DWT

The on-chip line buffer dominates the total area and power of line-based 2-D DWT. Therefore, the line buffer wordlength has to be carefully designed to maintain the quality level due to the dynamic range growing and the round-off errors. In this paper, a complete analysis methodology is proposed to derive the required wordlength of line buffer given the desired quality level of reconstructed image. The proposed methodology can guarantee to avoid overflow of coefficients, and the difference between predicted and experimental quality level is averagely 0.06 dB in terms of PSNR

Spatial-temporal consistent labeling for multi-camera multi-object surveillance systems

For an intelligent multi-camera multi-object surveillance system, object correspondence across time and space is important to many smart visual applications. In this paper, we propose a temporal and spatial consistent labeling algorithm for this demand. In the algorithm, an object corresponding database records the temporal and spatial consistency information for each segmented mask. With the database, the object-mask correlations are propagated through the propagation rules by analyzing mask splitting/merging conditions. In the spatial consistent labeling method, the homography warping and the earth movers distance are adopted to match same objects across different views. The earth movers distance solves the double matching problem, allows the algorithm to work normally under a small deviation of detected object locations, and makes pairing results have minimum global matching distances. The concept trusting-former- pairs-more is also adopted to avoid frequent pair switching if two objects are too close. The correct spatial labeling rate is about 89.25% in average. For online processing applications, the algorithm need not trace back to the past frames. The overall processing speed is about 10.24 frame per second (fps) with CIF size video running on a 2.8GHz general purpose CPU.

Architecture of MPEG-7 color structure description generator for realtime video applications

Color structure descriptor (CSD) provides satisfactory image indexing and retrieval results among all color-based descriptors in MPEG-7. The superiority comes from the consideration of space distribution of colors. Hardware accelerator is a must because its good performance is at the expense of high computational complexity. In this paper, a design approach of specific hardware accelerators for descriptors is explored. The characteristics of CSD algorithm are also analyzed and an efficient architecture is proposed. The proposed architecture can generate CSD description of 256 256 image at 30 frames per second (fps). The architecture provides about 4.5 giga instructions per second (GIPS) to achieve real-time applications like assisting rate control in video coding system and circumstance change detection in surveillance system.