Nurulfajar Abd Manap

Smart surveillance system based on stereo matching algorithms with IP and PTZ cameras

In this paper, we describe a system for smart surveillance using stereo images with applications to advanced video surveillance systems. The system utilizes two smart IP cameras to obtain the position and location of objects. In this case, the object target is human face. The position and location of the object are automatically extracted from two IP cameras and subsequently transmitted to an ACTi Pan-Tilt-Zoom (PTZ) camera, which then points and zooms to the exact position in space. This work involves video analytics for estimating the location of the object in a 3D environment and transmitting its positional coordinates to the PTZ camera. The research consists of algorithms development in surveillance system including face detection, block matching, location estimation and implementation with ACTi SDK tool. The final system allows the PTZ camera to track the objects and acquires images in high-resolution quality.

Novel view synthesis based on depth map layers representation

This paper presents a method that jointly performs stereo matching and inter-view interpolation to obtain the depth map and virtual view image. A novel view synthesis method based on depth map layers representation of the stereo image pairs is proposed. The main idea of this approach is to separate the depth map into several layers of depth based on the disparity distance of the corresponding points. The novel view synthesis can be interpolated independently to each layer of depth by masking the particular depth layer. The final novel view synthesis obtained with the entire layers flattens into a single layer. Since the image view synthesis is performed in separate layers, the extracted new virtual object can be superimposed onto another 3D scene. The method is useful for free viewpoint video application with a small number of camera configurations. Based on the experimental results, it shows that the algorithm could improve the efficiency of finding the depth map and to synthesis the new virtual view images.

Depth Image Layers Separation (DILS) algorithm of image view synthesis based on stereo vision

A new Depth Image Layers Separation (DILS) algorithm for synthesizing inter-view images based on disparity depth map layers representation is presented. The approach is to separate the depth map into several layers identified through histogram-based clustering. Each layer is extracted using inter-view interpolation to create objects based on location and depth. DILS is a new paradigm in selecting interesting image locations based on depth, but also in producing new image representations that allow objects or parts of an image to be described without the need of segmentation and identification. The image view synthesis can reduce the configuration complexity of multi-camera arrays in 3D imagery and free-viewpoint applications. The simulation results show that depth layer separation is able to create inter-view images that may be integrated with other techniques such as occlusion handling processes. The DILS algorithm can be implemented using both simple as well as sophisticated stereo matching methods to synthesize inter-view images.

Low cost multi-view video system for wireless channel

With the advent in display technology, the 3DTV will provide a new viewing experience without the need of wearing special glasses to watch the 3D scenes. One of the key elements in 3DTV is the multi-view video coding, obtained from a set of synchronized cameras, capture the same scene from different view points. The video streams are synchronized and subsequently used to exploit the redundancy contained among video sources. A multi-view video consists of components for data acquisition, compression, transmission and display. This paper outlines the design and implementation of a multi-view video system for transmission over a wireless channel. Synchronized video sequences acquired from four separate cameras and coded with H.264/AVC. The video data is then transmitted over a simulated Rayleigh channel through Digital Video Broadcasting -Terrestrial (DVB-T) system with Orthogonal Frequency Division Multiplexing (OFDM).

Co-operative surveillance cameras for high quality face acquisition in a real-time door monitoring system

The increasing number of CCTV cameras in use poses a problem of information overloading for end users. Smart technologies are used in video surveillance to automatically analyze and detect events of interest in real-time, through 2D and 3D video processing techniques called video analytics. This paper presents a smart surveillance stereo vision system for real-time intelligent door access monitoring. The system uses two IP cameras in a stereo configuration and a pan-tilt-zoom (PTZ) camera, to obtain real-time localised, high quality images of any triggering events.

Face detection and stereo matching algorithms for smart surveillance system with IP cameras

In this paper, we describe a smart surveillance system to detect human faces in stereo images with applications to advanced video surveillance systems. The system utilizes two smart IP cameras to obtain the position and location of the object that is a human face. The position and location of the object are extracted from two IP cameras and subsequently transmitted to a Pan-Tilt-Zoom (PTZ) camera, which can point to the exact position in space. This work involves video analytics for estimating the location of the object in a 3D environment and transmitting its positional coordinates to the PTZ camera. The research consists of algorithm development in surveillance system including face detection, stereo matching, location estimation and implementation with ACTi PTZ camera. The final system allows the PTZ camera to track the objects and acquires images in high-resolution.

Evaluation of dynamic programming among the existing stereo matching algorithms

There are various types of existing stereo matching algorithms on image processing which applied on stereo vision images to get better results of disparity depth map. One of them is the dynamic programming method. On this research is to perform an evaluation on the performance between the dynamic programming with other existing method as comparison. The algorithm used on the dynamic programming is the global optimization which provides better process on stereo images like its accuracy and its computational efficiency compared to other existing stereo matching algorithms. The dynamic programming algorithm used on this research is the current method as its disparity estimates at a particular pixel and all the other pixels unlike the old methods which with scanline based of dynamic programming. There will be details on every existing methods presented on this paper with the comparison between the dynamic programming and the existing methods. This can propose the dynamic programming method to be used on many applications in image processing.

Multi-Level View Synthesis (MLVS) based on Depth Image Layer Separation (DILS) algorithm for multi-camera view system

A novel Multi-Level View Synthesis (MLVS) approach for 3D vision and free-viewpoint video applications, such as light field imaging, is presented. MLVS exploits the advantages of Depth Image Layer Separation (DILS), a new inter-view interpolation algorithm, by extending stereo to multiple camera configurations. The technique finds the pixel correspondences and synthesis through two levels of matching and synthesis process. The main aim of MLVS is to create a multi-camera view system through a reduced number of actual image acquisition cameras, whilst maintaining the quality of the virtual view synthesis images. The proposed technique is shown to offer improved performance and provide additional views with fewer cameras compared to conventional high volume camera configurations for free-viewpoint video acquisition. Thus, substantial cost savings can ensue in processing, calibration, bandwidth and storage requirements.