Abstract: This paper presents a real time video surveillance system which is capable of tracking multiple real time objects using Polar Vector Median (PVM) and Block Coding Modes (BCM) with Global Motion Compensation (GMC). This strategy works in the packed area and furthermore utilizes the movement vectors and BCM from the compressed bit stream to perform real time object tracking. We propose to do this in view of the neighboring Motion Vectors (MVs) using a method called PVM. Since GM adds to the object’s native motion, for accurate tracking, it is important to remove GM from the MV field prior to further processing. The proposed method is tested on a number of standard sequences and the results show its advantages over some of the current modern methods.
Abstract: In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through different levels of alert according to the estimated distance. Due to the low complexity and computational cost, the proposed system ensures real time performances.
Abstract: This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.
Abstract: Human action is recognized directly from the video sequences. The objective of this work is to recognize various human actions like run, jump, walk etc. Human action recognition requires some prior knowledge about actions namely, the motion estimation, foreground and background estimation. Region of interest (ROI) is extracted to identify the human in the frame. Then, optical flow technique is used to extract the motion vectors. Using the extracted features similarity measure based classification is done to recognize the action. From experimentations upon the Weizmann database, it is found that the proposed method offers a high accuracy.
Abstract: In this paper, we present the design of the
super-ellipsoidal potential function (SEPF), that can be used for
autonomous collision avoidance of an unmanned aerial vehicle (UAV)
in a 3-dimensional space. In the design of SEPF, we have the
full control over the shape and size of the potential function. In
particular, we can adjust the length, width, height, and the amount
of flattening at the tips of the potential function so that the collision
avoidance motion vector generated from the potential function can
be adjusted accordingly. Based on the idea of the SEPF, we also
propose an approach for the local autonomy of a UAV for its collision
avoidance when the UAV is teleoperated by a human operator. In
our proposed approach, a teleoperated UAV can not only avoid
collision autonomously with other surrounding objects but also track
the operator’s control input as closely as possible. As a result, an
operator can always be in control of the UAV for his/her high-level
guidance and navigation task without worrying too much about
the UAVs collision avoidance while it is being teleoperated. The
effectiveness of the proposed approach is demonstrated through a
human-in-the-loop simulation of quadrotor UAV teleoperation using
virtual robot experimentation platform (v-rep) and Matlab programs.
Abstract: In this paper a new Joint Adaptive Block Matching
Search (JABMS) algorithm is proposed to generate motion vector
and search a best match macro block by classifying the motion vector
movement based on prediction error. Diamond Search (DS)
algorithm generates high estimation accuracy when motion vector is
small and Adaptive Rood Pattern Search (ARPS) algorithm can
handle large motion vector but is not very accurate. The proposed
JABMS algorithm which is capable of considering both small and
large motions gives improved estimation accuracy and the
computational cost is reduced by 15.2 times compared with
Exhaustive Search (ES) algorithm and is 1.3 times less compared
with Diamond search algorithm.
Abstract: Full search block matching algorithm is widely used for hardware implementation of motion estimators in video compression algorithms. In this paper we are proposing a new architecture, which consists of a 2D parallel processing unit and a 1D unit both working in parallel. The proposed architecture reduces both data access power and computational power which are the main causes of power consumption in integer motion estimation. It also completes the operations with nearly the same number of clock cycles as compared to a 2D systolic array architecture. In this work sum of absolute difference (SAD)-the most repeated operation in block matching, is calculated in two steps. The first step is to calculate the SAD for alternate rows by a 2D parallel unit. If the SAD calculated by the parallel unit is less than the stored minimum SAD, the SAD of the remaining rows is calculated by the 1D unit. Early termination, which stops avoidable computations has been achieved with the help of alternate rows method proposed in this paper and by finding a low initial SAD value based on motion vector prediction. Data reuse has been applied to the reference blocks in the same search area which significantly reduced the memory access.
Abstract: Super resolution (SR) technologies are now being
applied to video to improve resolution. Some TV sets are now
equipped with SR functions. However, it is not known if super
resolution image reconstruction (SRR) for TV really works or not.
Super resolution with non-linear signal processing (SRNL) has
recently been proposed. SRR and SRNL are the only methods for
processing video signals in real time. The results from subjective
assessments of SSR and SRNL are described in this paper. SRR video
was produced in simulations with quarter precision motion vectors and
100 iterations. These are ideal conditions for SRR. We found that the
image quality of SRNL is better than that of SRR even though SRR
was processed under ideal conditions.
Abstract: Multimedia information availability has increased
dramatically with the advent of video broadcasting on handheld
devices. But with this availability comes problems of maintaining the
security of information that is displayed in public. ISMA Encryption
and Authentication (ISMACryp) is one of the chosen technologies for
service protection in DVB-H (Digital Video Broadcasting-
Handheld), the TV system for portable handheld devices. The
ISMACryp is encoded with H.264/AVC (advanced video coding),
while leaving all structural data as it is. Two modes of ISMACryp are
available; the CTR mode (Counter type) and CBC mode (Cipher
Block Chaining) mode. Both modes of ISMACryp are based on 128-
bit AES algorithm. AES algorithms are more complex and require
larger time for execution which is not suitable for real time
application like live TV. The proposed system aims to gain a deep
understanding of video data security on multimedia technologies and
to provide security for real time video applications using selective
encryption for H.264/AVC. Five level of security proposed in this
paper based on the content of NAL unit in Baseline Constrain profile
of H.264/AVC. The selective encryption in different levels provides
encryption of intra-prediction mode, residue data, inter-prediction
mode or motion vectors only. Experimental results shown in this
paper described that fifth level which is ISMACryp provide higher
level of security with more encryption time and the one level provide
lower level of security by encrypting only motion vectors with lower
execution time without compromise on compression and quality of
visual content. This encryption scheme with compression process
with low cost, and keeps the file format unchanged with some direct
operations supported. Simulation was being carried out in Matlab.
Abstract: In 3D-wavelet video coding framework temporal
filtering is done along the trajectory of motion using Motion
Compensated Temporal Filtering (MCTF). Hence computationally
efficient motion estimation technique is the need of MCTF. In this
paper a predictive technique is proposed in order to reduce the
computational complexity of the MCTF framework, by exploiting
the high correlation among the frames in a Group Of Picture (GOP).
The proposed technique applies coarse and fine searches of any fast
block based motion estimation, only to the first pair of frames in a
GOP. The generated motion vectors are supplied to the next
consecutive frames, even to subsequent temporal levels and only fine
search is carried out around those predicted motion vectors. Hence
coarse search is skipped for all the motion estimation in a GOP
except for the first pair of frames. The technique has been tested for
different fast block based motion estimation algorithms over different
standard test sequences using MC-EZBC, a state-of-the-art scalable
video coder. The simulation result reveals substantial reduction (i.e.
20.75% to 38.24%) in the number of search points during motion
estimation, without compromising the quality of the reconstructed
video compared to non-predictive techniques. Since the motion
vectors of all the pair of frames in a GOP except the first pair will
have value ±1 around the motion vectors of the previous pair of
frames, the number of bits required for motion vectors is also
reduced by 50%.
Abstract: Wireless capsule Endoscopy (WCE) has rapidly
shown its wide applications in medical domain last ten years
thanks to its noninvasiveness for patients and support for thorough
inspection through a patient-s entire digestive system including
small intestine. However, one of the main barriers to efficient
clinical inspection procedure is that it requires large amount of
effort for clinicians to inspect huge data collected during the
examination, i.e., over 55,000 frames in video. In this paper, we
propose a method to compute meaningful motion changes of
WCE by analyzing the obtained video frames based on regional
optical flow estimations. The computed motion vectors are used to
remove duplicate video frames caused by WCE-s imaging nature,
such as repetitive forward-backward motions from peristaltic
movements. The motion vectors are derived by calculating
directional component vectors in four local regions. Our
experiments are performed on small intestine area, which is of
main interest to clinical experts when using WCEs, and our
experimental results show significant frame reductions comparing
with a simple frame-to-frame similarity-based image reduction
method.
Abstract: One of the popular methods for recognition of facial
expressions such as happiness, sadness and surprise is based on
deformation of facial features. Motion vectors which show these
deformations can be specified by the optical flow. In this method, for
detecting emotions, the resulted set of motion vectors are compared
with standard deformation template that caused by facial expressions.
In this paper, a new method is introduced to compute the quantity of
likeness in order to make decision based on the importance of
obtained vectors from an optical flow approach. For finding the
vectors, one of the efficient optical flow method developed by
Gautama and VanHulle[17] is used. The suggested method has been
examined over Cohn-Kanade AU-Coded Facial Expression Database,
one of the most comprehensive collections of test images available.
The experimental results show that our method could correctly
recognize the facial expressions in 94% of case studies. The results
also show that only a few number of image frames (three frames) are
sufficient to detect facial expressions with rate of success of about
83.3%. This is a significant improvement over the available methods.
Abstract: In this paper a fast motion estimation method for
H.264/AVC named Triplet Search Motion Estimation (TS-ME) is
proposed. Similar to some of the traditional fast motion estimation
methods and their improved proposals which restrict the search points
only to some selected candidates to decrease the computation
complexity, proposed algorithm separate the motion search process to
several steps but with some new features. First, proposed algorithm try
to search the real motion area using proposed triplet patterns instead of
some selected search points to avoid dropping into the local minimum.
Then, in the localized motion area a novel 3-step motion search
algorithm is performed. Proposed search patterns are categorized into
three rings on the basis of the distance from the search center. These
three rings are adaptively selected by referencing the surrounding
motion vectors to early terminate the motion search process. On the
other hand, computation reduction for sub pixel motion search is also
discussed considering the appearance probability of the sub pixel
motion vector. From the simulation results, motion estimation speed
improved by a factor of up to 38 when using proposed algorithm than
that of the reference software of H.264/AVC with ignorable picture
quality loss.
Abstract: Motion estimation is a key problem in video
processing and computer vision. Optical flow motion estimation can
achieve high estimation accuracy when motion vector is small.
Three-step search algorithm can handle large motion vector but not
very accurate. A joint algorithm was proposed in this paper to
achieve high estimation accuracy disregarding whether the motion
vector is small or large, and keep the computation cost much lower
than full search.
Abstract: Motion estimation is the most computationally
intensive part in video processing. Many fast motion estimation
algorithms have been proposed to decrease the computational
complexity by reducing the number of candidate motion vectors.
However, these studies are for fast search algorithms themselves while
almost image and video compressions are operated with software
based. Therefore, the timing constraints for running these motion
estimation algorithms not only challenge for the video codec but also
overwhelm for some of processors. In this paper, the performance of
motion estimation is enhanced by using Intel's Streaming SIMD
Extension 2 (SSE2) technology with Intel Pentium 4 processor.