The proposed algorithm relies on the MV output from video encoders that conform to
the H.264/AVC standard, it is likely that the encoder will be phased out sometime in
the future and be replaced by encoders of newer standard to cope with the ever
increasing demands for higher screen resolution and coding efficiency. The block
based MV output format used in the proposed algorithm ensures the extensibility of the
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7.8.1 Comparison to H.265/HEVC Encoding Standard
Comparing with H.264/AVC standard, the emerging High Efficiency Video Coding
(HEVC) standard can reduce video bit rate to up to 50% without loss of video quality
(Sullivan and Ohm et al., 2012). The different arrangements in block structure for the
two encoding standards are shown in Figure 7-5. As shown in the figure, the major
difference between H.264/AVC and HEVC standard is that the coding block size in
H.264/AVC is fixed at 16x16, while it can be 8x8 to 64x64 in HEVC. The variable
block size in HEVC is known as Coding Unit (CU) that shown in the Quadtree Coding
Structure in Figure 7-5. The selection of block size for motion estimation in HEVC
standard is arranged in a coding tree unit (CTU) and coding tree block (CTB) structure.
One frame is divided into a series of non-overlapped CTU. The size of a CTB can be
chosen as 16x16, 32x32 or 64x64 samples. The CTB may contain one or multiple
coding units (CUs). Similarly, each CU may contain one or multiple prediction units
(PUs). The size of each PU varies from 64x64 down to 4x4 samples (Sullivan and Ohm
et al., 2012).
Figure 7-5: Comparison of block structure for H.264/AVC and HEVC
In addition to the motion estimation process to find the MV to relate the current frame
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encoders. No motion information is present in this SKIP mode. The information for the
block concerned is obtained from the co-located block in the previous frame. In
contrast, MVs in HEVC are evaluated by either spatial or temporal approach. For an
intercoded PU, the encoder can decide to use motion estimation mode or motion merge
mode.
The motion estimation mode is the same as that in H.264/AVC encoders. It evaluates
the motion vectors according to images from previous frames. Motion merge mode is
newly introduced in HEVC, which is an improvement on SKIP mode. A set of
previously coded neighbouring PUs is used to form a list of candidates that are either
spatially or temporally close to the current PU. After deciding which candidate in the
list is suitable to be used, the motion information of the selected candidate is used
directly for the current PU. Therefore, the index of the selected candidate in the list is
encoded; no intensive motion search algorithm is required. By encoding only the index,
very few bits are required to code the difference between frames.
Bi-prediction motion estimation is employed in both H.264/AVC and HEVC. It makes
use of two sets of motion data to generate two MVs from different reference images.
The resultant motion compensated block is the weighted sum of the two motion
compensated blocks using the two MVs. Different weight can be applied to the two
motion compensated blocks in order to accommodate for different scenarios, such as
reflections and sudden light intensity changes.
Although there are different motion estimation algorithms available in the free
reference software for HEVC and H.264/AVC encoders, they are provided for
reference only. Among the motion estimation algorithms available in the reference
encoder software, Test Zone Search (TZS) algorithm is provided as a reference fast
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there is no specified motion estimation algorithm for the video standards, many motion
estimation methods have been studied and proposed by many researchers to achieve
different computation complexity and video quality targets.
The increased coding efficiency in HEVC is the result of increased encoder complexity.
The high computational cost on mode decision and motion estimation require
parallelised hardware and more computationally efficient algorithms to enable the
HEVC encoders to be used for real-time applications.
7.8.2 Shared-Use of Motion Vector from HEVC Encoder
Although the complexity of the HEVC encoder has considerably increased to achieve a
higher coding efficiency, it can be regarded as an improvement based on the
experience gained from previous coding standards, such as H.264/AVC. One of the
most important observations is that both H.264/AVC and HEVC encoders work by
dividing one frame into multiple non-overlapping small blocks. The motion estimation
process will also output MVs with different block size to best represent the underlying
motions of objects in the screen.
The block size of MV used in the proposed algorithm is 8x8 samples, the HEVC
encoder can be modified to output inter-frame MV of block size 8x8, using the method
proposed in Chapter 3.1.1. With the MV output from the HEVC encoder following the
format proposed in this project, the algorithm can be extended to be used in newer
generation video encoders. The computation cost for motion estimation in the HEVC
encoder can also be enhanced by making use of the information from the inertial
sensors and vehicle speed sensor. The efforts paid on enhancing H.264/AVC encoders
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7.9 Chapter Summary
This Chapter has elaborated the potential improvements that can be made to the
proposed algorithm. These include an improved camera calibration method, road region
detection with temporal consistency consideration, adaptive ego vehicle speed region of
interest segmentation and adding symmetry detection for slow relative speed vehicle
detection. For relatively fast speed moving object detection, adding predictive algorithm
to the estimation of displacement of MVs, faster template matching algorithm, and
rejection of non-critical detected objects by temporal movement evaluation, can be
considered to improve the detection rate and computational speed, as well as to reduce
the false alarm rate. Improvements to the motion estimation algorithm in the H.264/AVC
encoder, and future extension in using the MVs from the newer HEVC encoder are also
considered. With continuous efforts putting to the research on ADAS, these suggested
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8 Future R&D Directions
The future R&D direction will be to refine the performance of the developed algorithms
in terms of detection rate, false positive rate, as well as computation efficiency. Potential
improvements mentioned in Chapter 7 will be realised to improve the performance.
Since HEVC is the standard for next generation high-definition video, the future R&D
direction will be on better integration of the developed algorithm with HEVC. There
have been studies on the use of inertial sensors to reduce the computational cost on
motion estimation for video encoders (Chen and Zhao et al., 2011, Angelino and Cicala
et al., 2013, Wang and Ma et al., 2012). It is expected that the use of inertial sensors and
speed sensors can reduce the computation cost of HEVC for automotive applications.
Since the motion prediction can be taken from these sensors, it is expected that the
resulting MVs can describe the movements of objects more accurately without loss of
video compression efficiency. A new System-on-Chip with HEVC encoding making use
of sensor inputs can be less computationally expensive. The power consumption for
video encoding can also be reduced. This design will not only be beneficial to
automobiles looking for lower power consumption, but also to battery powered handheld
devices such as cameras and smartphones.
Working with multiple systems in a vehicle is another direction that needs to be
addressed. Currently, the system assumes there is no other system that outputs warnings
or overrides controls from the driver. The complicated on-board automobile system will
include a human-machine-interface that integrates all warnings, system status, and
available user preferences. The strategies on warning outputs, communication and
coordination among different driver assistance systems are also required to be