Technology has advanced in recent years to the point where multimedia communicators are beginning to emerge. These communicators are low-power, portable devices that can transmit and receive multimedia data through the wireless network. Due to the high computational complexity involved and the low-power constraint in wireless applications, these devices require the use of processors that are powerful and are at the same time very power-efficient. In order to facilitate interoperability, it is important that these devices use standardized compression and communication algorithms. As a first step in implementing multimedia terminals, Texas Instruments (TI) has demonstrated real-time MPEG-4 video decoding (simple profile) on TMS320C54x, TI's low power, high performance DSP chip. In addition, TI has outlined a system-level solution to transmitting video across wireless networks, including channel coding and communication protocols.

This paper presents a programmable DSP platform for digital still cameras based on the Texas Instruments TMS320C54x family. One major advantage of this platform is that, after capturing an image from a CCD sensor, processing the raw image, and compressing the image for storage is performed on the digital signal processor (DSP). This provides a short shot-to-shot delay and a high degree of flexibility. The system realized also allows instant viewing and selective storing of captured images. This paper outlines the various processing stages necessary to take the raw CCD data and produce a JPEG compressed bit stream and highlighting the advantages of DSPs for this application. The programmable nature of this platform allows for the exploration of different image processing and compression techniques. The low power nature of the digital signal processor provides long battery life.

The MPEG-4 video compression standard incorporates several techniques to create error-resilient coded video. These techniques are effective against a certain level of errors. However, wireless channels often have very high error rates; thus channel coding is needed to reduce the number of errors in the compressed bitstream that is sent to the MPEG-4 video decoder. The structure of an MPEG-4 compressed bitstream lends itself to using unequal error protection to ensure fewer errors in the important portions of the bitstream. This paper discuses how unequal error protection can be used with the MPEG-4 error resilience tools and describes several experiments using both unequal and equal error protection on video sent through a simulated GSM channel. The results of these experiments show that when the bit error rate is high, unequal error protection can improve reconstructed video quality by as much as 1 dB compared with equal error protection.

This paper describes an object-based video coding scheme (OBVC) that was proposed by Texas Instruments to the emerging ISO MPEG-4 video compression standardization effort. This technique achieves efficient compression by separating coherently moving objects from stationary background and compactly representing their shape, motion, and the content. In addition to providing improved coding efficiency at very low bit rates, the technique provides the ability to selectively encode, decode, and manipulate individual objects in a video stream. This technique supports all three MPEG-4 functionalities tested in the November 1995 tests, namely, improved coding efficiency, error resilience, and content scalability. This paper also describes the error protection and concealment schemes that enable robust transmission of compressed video over noisy communication channels such as analog phone lines and wireless links. The noise introduced by the communication channel is characterized by both burst errors and random bit errors. Applications of this object-based video coding technology include videoconferencing, video telephony, desktop multimedia, and surveillance video.

This paper describes a hybrid object-based video coding scheme that achieves efficient compression by separating coherently moving objects from stationary background and compactly representing their shape, motion and the content. In addition to providing improved coding efficiency at very low bit rates the technique provides the ability to selectively encode, decode and manipulate individual objects in a video stream. Applications of this object-based video coding technology include videoconferencing, videotelephony, desktop multimedia and surveillance video.

The problem of establishing reliable and accurate correspondence between a stored 3-D model and a 2-D image of it is important in many computer vision tasks, including model-based object recognition, autonomous navigation, pose estimation, airborne surveillance, and reconnaissance. This paper presents an approach to solving this problem in the context of autonomous navigation of a mobile robot in an outdoor urban, man-made environment. The robot's environment is assumed consist of polyhedral buildings. The 3-D descriptions of the lines constituting the buildings' rooftops is assumed to be given as the world model. The robot's position and pose are estimated by establishing correspondence between the straight line features extracted from the images acquired by the robot and the model features. The correspondence problem is formulated as a two-stage constrained search problem. Geometric visibility constraints are used to reduce the search space of possible model-image feature correspondences. Techniques for effectively deriving and capturing these visibility constraints from the given world model are presented. The position estimation technique presented is shown to be robust and accurate even in the presence of errors in the feature detection, incomplete model description, and occlusions. Experimental results of testing this approach using a model of an airport scene are presented.

The use of computer graphics in estimating the position of an autonomous mobile robot navigating in an outdoor mountainous environment is discussed. A digital elevation map (DEM) of the area in which the robot is to navigate is given, and the robot is equipped with a camera that can be panned and tilted, a compass, and an altimeter. The position of the robot is estimated by establishing a correspondence between the images acquired by the camera on the robot (actual images) and the images generated from the DEM (predicted images) using computer graphics techniques. Features are extracted from the predicted images and the actual images that are used in establishing the correspondence. The features used are the horizon line contours (HLCs) in the images. To reduce the search space a constrained search paradigm is used. Geometric constraints help prune the search space significantly.>

Describes a new method of tracking targets across a sequence of images and estimating the range of these tracked objects from the camera. The motion of the camera between the successive frames is assumed to be known. The distance from the sensor to the objects is assumed to be much larger than the physical dimensions of the object. the approach presented makes use of the known sensor motion to generate expected images which are then used in establishing a reliable correspondence and in tracking the targets across the image sequence. A mean normalized area correlation method is used to establish the inter-frame correspondence. Once this correspondence is established, two new methods of estimating the range of the target from the sensor are also developed. The techniques developed are tested with good success rate on a sequence of real aerial images.>

The position estimation problem for an autonomous land vehicle navigating in an unstructured mountainous terrain is solved. A digital elevation map (DEM) of the area is assumed to be given. It is also assumed that the robot is equipped with a camera that can be panned and tilted, a compass, and an altimeter. No recognizable landmarks are assumed to be present, and the robot is not assumed to have an initial estimate of its position. The solution structures the problem as a constrained search paradigm by searching the DEM for the possible robot location. The shape and position of the horizon line in the image plane and the known camera geometry of the perspective projection are used as parameters. Geometric constraints are used to prune the search space significantly. The algorithm is made robust to errors in the imaging process by accounting for worst case errors. The approach is tested using real terrain data of areas in Colorado and Texas.>

A technique is presented for estimating the position and pose of an autonomous mobile robot navigating in an outdoor, urban environment consisting of polyhedral buildings. The 3-D description of the roof tops of the buildings are assumed to be given as a world model. A discussion is presented of the uses of an intermediate representation of the environment, called the edge visibility regions (EVRs), in the positional estimation process.>

Presents a technique for estimating the position and pose of an autonomous mobile robot navigating in an outdoor, urban environment consisting of polyhedral buildings. The 3D descriptions of the rooftops of the buildings are assumed to be given as a world model. The robot is assumed to be equipped with a visual camera. The position and pose are estimated by establishing a correspondence between the lines that constitute the rooftops of the buildings (world model features) and their images. A constrained search paradigm is used to isolate a consistent set of correspondences. The geometric constraints between the world model features and their images are used to prune the search space. To effectively capture the geometric relations between the world model features with respect to their visibility from various positions of the robot in the plane in which it navigates (visibility plane), the free space of the robot is partitioned into a set of distinct, nonoverlapping regions called the edge visibility regions (EVRs). The use of these EVRs in isolating a consistent set of correspondences between the world model and the image features is discussed.>