Implementation of Face Detection and Tracking on A Low Cost Embedded System Using Fusion Technique

Abstract—This paper presents the fusion techniques for detecting and tracking the face. The proposed method combines the Viola-Jones method, the CamShift tracking, and the Kalman Filter tracking. The objective is to increase the face detection rate, while reduce the computation cost. The proposed method is implemented on a low cost embedded system based-on the Raspberry Pi module. The experimental results show that the average detection rate of 98.3% is achieved, and it is superior compared to the existing techniques. The proposed system achieves the frame rate of 7.09 fps in the real-time face detection. Index Terms—Face detection, Viola-Jones, CamShift, Kalman Filter, Raspberry Pi

Détection et suivi du visage et des mains appliqués à la surveillance de prise de médicaments

Surveillance de la prise de médicament -- Détection et suivi -- Reconnaissance d'activité humaine -- Aperçu de la méthode -- Hypothèse et cadre d'application -- Détection des régions de peau -- Occlusion entre les régions de la peau -- Détection et suivi du visage -- Détection et suivi des mains -- Détection et suivi des bouteilles de médicaments -- Temps d'exécution

Sistem Pemandu Pengemudi Berbasis Kamera Embeded

Keamanan dan kenyamanan berkendara merupakan salah satu aspek penting yang harus diperhatikan oleh industri otomotif. Sebuah sistem yang mampu memberikan peringatan dini pada pengemudi akan membantu mencegah terjadinya kecelakaan. Sistem pemandu pengemudi (Driver assistance system) merupakan sistem yang dikembangkan untuk menyediakan fungsi tersebut. Sistem pemandu pengemudi berbasis kamera merupakan sistem yang berkembang cukup pesat, seiring dengan perkembangan teknologi di bidang teknik pengolahan citra digital dan sistem komputer. Penelitian ini bertujuan untuk mengembangkan sistem pemandu pengemudi berbasis kamera yang mampu mendeteksi kelelahan dan konsentrasi/pandangan mata pengemudi, rambu-rambu lalu lintas, dan marka jalan, serta objek atau kendaraan yang berada di depan. Pada peneltian di tahun pertama, dikembangkan sistem pendeteksi kelelahan pengemudi menggunakan kamera embeded yang dipasang di ruang kemudi kendaraan. Sebuah sistem komputer embeded digunakan sebagai pengolah utama dalam proses pendeteksian berbasis kamera tersebut. Dengan menggunakan sistem embeded ini, implementasi sistem di kendaraan dapat dilakukan dengan mudah dan murah

Unmanned aerial vehicle large scale mapping for coastal erosion assessment

Most of the time, many countries in tropical region are covered by cloudwhich obstruct the acquisition of high resolution optical image from satellite. Thus,the application of large scale mapping for coastal erosion assessment is difficult to becarried out. The unmanned aerial vehicle (UAV) can be used for acquisition of highresolution image due to its ability of flying at low altitudes and under cloud cover.This study aims to improve the methodology of data acquisition for assessing erodedcoastal area by using UAV system designed for large scale mapping. The objectivesof this study are (i) to improve the methodology of data acquisition for large scalecoastal erosion assessment using UAV with rapid and low cost, (ii) to assess theaccuracy of the digital photogrammetric products obtained with different groundcontrol points (GCP) configurations and flying altitude, and (iii) to identify andassess coastal areas due to erosion based on the large-scale orthophoto produced.Two improved methods were introduced in this study: (i) rapid data acquisition andprocessing, low cost and accurate mapping using UAV, and (ii) modification of theend point rate (EPR) and linear regression rate (LRR) calculation methods byincluding two new parameters namely the sea water and wave level to detectcoastline changes. The modified EPR and LRR methods in detecting the coastlinechanges of Crystal Bay, Alai, Melaka and Kampung Seri Pantai, Mersing, Johorwere evaluated through statistical model, namely t-test and compared with otherstudies of similar area for validation and verification. Several configurations of GCP,check points (CP) and flying altitude were used to produce the digital elevationmodel (DEM) and orthophoto which were then processed photogrammetrically.Subsequently, the coastal erosion assessment was performed and the coastlinechanges of private properties, buildings and residential areas was identified. Theresults show that the best GCP configuration to produce coastal erosion mappingscale of 1:14000 is 25 points. Meanwhile, the best flying altitude is 300m withaccuracies of ±0.002m, ±0.004m and ±0.389m in Northing, Easting and Heightrespectively. Furthermore, this study shows that most of the coastline, privateproperties, buildings and residential areas are affected by the coastal erosion. Basedon the modified EPR and LRR calculation methods in determining the coastlinechanges, it is evident that the coastline change rate is significant. In conclusion, thisstudy shows that the UAV system offers many advantages such as its ability to fly atlow altitude, low cost, rapid data acquisition and processing in detecting coastlinechanges and accurate results

Assessing the Impact of Active Signage Systems on Driving Behavior and Traffic Safety

Unsignalized Stop-Controlled Intersections (SCI) are widely used in North America, and account for one out of every ten collisions. Understanding how drivers and pedestrians behave at unsignalized intersections is critical for public safety. Drivers who do not obey the stop-sign’s indication by not coming to a complete stop or miss or fail to stop at SCI create a substantial safety risk. For decades, visibility and placement of road alignments and signage at intersections have been a concern among transportation safety specialists. Deployment of backlit Light-Emitting Diode (LED) or other illuminated signs (also known as active road signs) has been increased especially at hot-spots and locations with known safety problems, or potential collision risks. While these signs are expected to improve safety measures by regulating safe travelers’ passage, their performance is not yet fully understood. Although environmental factors such as intersection type, location, and road design are playing a major role, compositional variables such as driver behaviour, which can be explained in terms of carelessness, lack of attention, or overconfidence, is resulting in a failure to comply with the law of making a complete stop at SCI. Previous empirical research demonstrated some correlation between several variables such as traveller compliance with road signs and alignments, direct and indirect road safety measures, collision/conflict frequency, and road/traffic characteristics. These studies commonly employ before-after or cross-reference analyses to determine the long-term effects of various countermeasures at SCI. A few studies also utilized calibrated micro-simulations models to evaluate the surrogate safety measures at SCI. This thesis defines a methodology to evaluate the safety performance of a new and untested signage without putting traffic at long risk. To evaluate the performance of the signs, the suggested methodology investigates multiple parameters and identifies influencing variables in a conflict-based collision-prediction model at SCI. The proposed methodology is applied to a real-world network in the city of Montreal, with several three-leg SCI equipped with different countermeasures. The experiment was designed in a fashion which isolates the influence of several variables, allowing the focus to be on the impact of the target variable (signage type). Field experiments have been performed to study the driver’s behavior in terms of approaching speed as well as quantitative analysis on reactions to various signs, using different sample groups from the same population. This research sets up a microsimulation model that captures drivers’ behaviour with respect to signage according to the observed data. A genetic algorithm was deployed to calibrate the microsimulation model in terms of turning movement counts and the critical conflicts were calculated at each intersection using vehicle trajectories. Collision-prediction regression models was then developed for the intersections under investigation, using traffic volume and conflict. The results demonstrated a high correlation among countermeasures and drivers’ speed and compliance. The relationship between critical conflicts computed in microsimulation models and actual collisions was found to be statistically significant. The model which includes drivers' compliance in collision-prediction regression was also found to fit the collision data better. However, the results of this study do not support the previous assumption that the conflict-based collision-prediction models fit the collision data better than the volume-based collision-prediction models at SCI, especially with drivers’ compliance supplementary data. Finally, while the backlit signs’ performance was marginally better than that of a normal LED active sign, the difference was not statistically significant. The methodology suggested in this thesis has the potential to be implemented in safety performance evaluation of a countermeasure without placing traffic at danger for an extended period. For instance, when there is apprehension about an adverse effect. Future research could investigate leveraging drivers’ behaviour to countermeasures, to improve the performance of collision-prediction regression models like the one proposed in this thesis. Finally, the results from the performance assessment of the LED active signs can assist transportation specialists in deciding whether or not to deploy these countermeasures

Visual motion estimation and tracking of rigid bodies by physical simulation

This thesis applies knowledge of the physical dynamics of objects to estimating object motion from vision when estimation from vision alone fails. It differentiates itself from existing physics-based vision by building in robustness to situations where existing visual estimation tends to fail: fast motion, blur, glare, distractors, and partial or full occlusion. A real-time physics simulator is incorporated into a stochastic framework by adding several different models of how noise is injected into the dynamics. Several different algorithms are proposed and experimentally validated on two problems: motion estimation and object tracking. The performance of visual motion estimation from colour histograms of a ball moving in two dimensions is improved considerably when a physics simulator is integrated into a MAP procedure involving non-linear optimisation and RANSAC-like methods. Process noise or initial condition noise in conjunction with a physics-based dynamics results in improved robustness on hard visual problems. A particle filter applied to the task of full 6D visual tracking of the pose an object being pushed by a robot in a table-top environment is improved on difficult visual problems by incorporating a simulator as a dynamics model and injecting noise as forces into the simulator.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Simple and Complex Human Action Recognition in Constrained and Unconstrained Videos

Human action recognition plays a crucial role in visual learning applications such as video understanding and surveillance, video retrieval, human-computer interactions, and autonomous driving systems. A variety of methodologies have been proposed for human action recognition via developing of low-level features along with the bag-of-visual-word models. However, much less research has been performed on the compound of pre-processing, encoding and classification stages. This dissertation focuses on enhancing the action recognition performances via ensemble learning, hybrid classifier, hierarchical feature representation, and key action perception methodologies. Action variation is one of the crucial challenges in video analysis and action recognition. We address this problem by proposing the hybrid classifier (HC) to discriminate actions which contain similar forms of motion features such as walking, running, and jogging. Aside from that, we show and proof that the fusion of various appearance-based and motion features can boost the simple and complex action recognition performance. The next part of the dissertation introduces pooled-feature representation (PFR) which is derived from a double phase encoding framework (DPE). Considering that a given unconstrained video is composed of a sequence of simple frames, the first phase of DPE generates temporal sub-volumes from the video and represents them individually by employing the proposed improved rank pooling (IRP) method. The second phase constructs the pool of features by fusing the represented vectors from the first phase. The pool is compressed and then encoded to provide video-parts vector (VPV). The DPE framework allows distilling the video representation and hierarchically extracting new information. Compared with recent video encoding approaches, VPV can preserve the higher-level information through standard encoding of low-level features in two phases. Furthermore, the encoded vectors from both phases of DPE are fused along with a compression stage to develop PFR

Technology transfer practices and strategies: Issues for Nigerian construction organisations and for research

Technology transfer is increasingly being seen as an important issue for economic development and growth. Arguably, this is why developed and especially developing countries are very keen on technology transfer. However, there are those that contend that organisations in the Nigerian construction industry are not as engaged in technology transfer as many would like, and that potential benefits of doing so are not realized. In the same vein, the challenges that confront construction organisations in Nigeria in terms of technology transfer have received very little empirical studies. This paper, therefore, presents a thorough review of literature on strategic issues and choices that Nigerian construction organisations face in grappling with technology transfer, together with associated challenges. Consideration is also given to what technology transfer actually means to such organisations, and how this is viewed in line with other terms such as innovation. The paper argues and concludes that the challenges that confront construction organisations in Nigeria are multifaceted and likely to impact on their strategic choices. In the same vein, it is also argued that these have implications for researchers attempting to investigate technology transfer practices and strategies in construction organisations in Nigeria in terms of their choice of research strategy and design