A sensor aided H.264 encoder tested on aerial imagery for SFM

Email Print Request Permissions Standard video coding systems currently employed in UAV (Unmanned Aerial Vehicle) and aerial drone applications do not rely on some peculiarities in terms of scene 3D model and correlation among successive frames. In particular, the observed scene is static, i.e. the camera movement is dominant, and it can often be well approximated with a plane. Moreover, camera position and orientation can be obtained from the navigation system. Therefore, correspondent points on two video frames are linked by a simple homography. This paper presents novel results obtained by a low-complexity sensor aided H.264 encoder, recently developed at CIRA and yet tested on simulated data. The proposed encoder employs a new motion estimation scheme which make use of the global motion information provided by the onboard navigation system. The homography is used in order to initialize the block matching algorithm allowing a more robust motion estimation and a smaller search window, and hence reducing the complexity. The tests are made coding real aerial imagery, captured to be used for 3D scene reconstruction. The images are acquired by an high resolution camera mounted on a small drone, flying at low altitude

A SENSOR AIDED H.264/AVC VIDEO ENCODER FOR AERIAL VIDEO SEQUENCES WITH IN THE LOOP METADATA CORRECTION

Unmanned Aerial Vehicles (UAVs) are often employed to collect high resolution images in order to perform image mosaicking and/or 3D reconstruction. Images are usually stored on board and then processed with on-ground desktop software. In such a way the computational load, and hence the power consumption, is moved on ground, leaving on board only the task of storing data. Such an approach is important in the case of small multi-rotorcraft UAVs because of their low endurance due to the short battery life. Images can be stored on board with either still image or video data compression. Still image system are preferred when low frame rates are involved, because video coding systems are based on motion estimation and compensation algorithms which fail when the motion vectors are significantly long and when the overlapping between subsequent frames is very small. In this scenario, UAVs attitude and position metadata from the Inertial Navigation System (INS) can be employed to estimate global motion parameters without video analysis. A low complexity image analysis can be still performed in order to refine the motion field estimated using only the metadata. In this work, we propose to use this refinement step in order to improve the position and attitude estimation produced by the navigation system in order to maximize the encoder performance. Experiments are performed on both simulated and real world video sequence

Sensor aided H.264 video encoder for UAV applications

This paper presents a new low-complexity H.264 encoder for Unmanned Aerial Vehicles (UAV) applications. Standard video coding systems currently employed in UAV applications do not rely on some peculiarities in terms of scene 3D model and correlation among successive frames. In particular, the observed scene is static, i.e. the camera movement is dominant, and it can often be well approximated with a plane. Moreover, camera position and orientation can be obtained from the navigation system. Therefore, correspondent points on two video frames are linked by a simple homography. The encoder employs a new motion estimation scheme which make use of the global motion information provided by the onboard navigation system. The homography is used in order to initialize the block matching algorithm allowing a more robust motion estimation and a smaller search window, and hence reducing the complexity. Experimental results show that the proposed scheme ouperforms standard H.264 in terms of PSNR and throughput. The results are relevant in low frame rate video coding, which is a typical scenario in UAV behind line-of-sight (BLOS) missions. Experiments open new drections in developing new sensor aided video coding standard

Moving object detection for automobiles by the shared use of H.264/AVC motion vectors : innovation report.

Cost is one of the problems for wider adoption of Advanced Driver Assistance Systems (ADAS) in China. The objective of this research project is to develop a low-cost ADAS by the shared use of motion vectors (MVs) from a H.264/AVC video encoder that was originally designed for video recording only. There were few studies on the use of MVs from video encoders on a moving platform for moving object detection. The main contribution of this research is the novel algorithm proposed to address the problems of moving object detection when MVs from a H.264/AVC encoder are used. It is suitable for mass-produced in-vehicle devices as it combines with MV based moving object detection in order to reduce the cost and complexity of the system, and provides the recording function by default without extra cost. The estimated cost of the proposed system is 50% lower than that making use of the optical flow approach. To reduce the area of region of interest and to account for the real-time computation requirement, a new block based region growth algorithm is used for the road region detection. To account for the small amplitude and limited precision of H.264/AVC MVs on relatively slow moving objects, the detection task separates the region of interest into relatively fast and relatively slow speed regions by examining the amplitude of MVs, the position of focus of expansion and the result of road region detection. Relatively slow moving objects are detected and tracked by the use of generic horizontal and vertical contours of rear-view vehicles. This method has addressed the problem of H.264/AVC encoders that possess limited precision and erroneous motion vectors for relatively slow moving objects and regions near the focus of expansion. Relatively fast moving objects are detected by a two-stage approach. It includes a Hypothesis Generation (HG) and a Hypothesis Verification (HV) stage. This approach addresses the problem that the H.264/AVC MVs are generated for coding efficiency rather than for minimising motion error of objects. The HG stage will report a potential moving object based on clustering the planar parallax residuals satisfying the constraints set out in the algorithm. The HV will verify the existence of the moving object based on the temporal consistency of its displacement in successive frames. The test results show that the vehicle detection rate higher than 90% which is on a par to methods proposed by other authors, and the computation cost is low enough to achieve the real-time performance requirement. An invention patent, one international journal paper and two international conference papers have been either published or accepted, showing the originality of the work in this project. One international journal paper is also under preparation